2024-03-29T11:07:07Z
http://docs.lib.purdue.edu/do/oai/
oai:docs.lib.purdue.edu:jps-1000
2006-12-11T16:18:20Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Optimizing and “Pessimizing”: Human Performance with Instructional Variants of the Traveling Salesperson Problem
Chronicle, Edward
MacGregor, James
Ormerod, Thomas
travelling salesperson problem
heuristics
long and short tours
Article
The two-dimensional Traveling Salesperson Problem (TSP) requires finding the shortest tour through n locations. Untrained adults are adept at the task, and reliably outperform simple construction algorithms for n up to 60. Performance may stem from a specific, inherent ability. Alternatively, it may reflect general spatial intelligence, whether inherent or acquired. If the latter holds, then people should be equally adept at finding longest tours. Two experiments comparing ability in the two tasks found participants significantly better at finding short than long tours. Furthermore, human performance was significantly worse than a simple construction algorithm (furthest-neighbor) for the task of finding long tours. The result is consistent with the hypothesis of a specific, inherent ability to find short routes.
1
https://docs.lib.purdue.edu/jps/vol1/iss1/7
oai:docs.lib.purdue.edu:jps-1001
2007-06-19T15:08:52Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Measuring Human Performance on Clustering Problems: Some Potential Objective Criteria and Experimental Research Opportunities
Brusco, Michael
Human performance
clustering problems
Article
The study of human performance on discrete optimization problems has a considerable history that spans various disciplines. The two most widely studied problems are the Euclidean traveling salesperson problem and the quadratic assignment problem. The purpose of this paper is to outline a program of study for the measurement of human performance on discrete optimization problems related to clustering of points in the two-dimensional plane. I describe possible objective criteria for clustering problems, the measurement of agreement of solutions produced by subjects, and categories of experiments for investigating human performance on clustering problems.
1
https://docs.lib.purdue.edu/jps/vol1/iss2/5
oai:docs.lib.purdue.edu:jps-1003
2006-12-05T20:16:18Z
publication:jps
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publication:libraries
publication:pupoaj
Are Individual Differences in Performance on Perceptual and Cognitive Optimization Problems Determined by General Intelligence?
Burns, Nicholas R.
Lee, Michael D.
Vickers, Douglas
Article
Studies of human problem solving have traditionally used deterministic tasks that require the execution of a systematic series of steps to reach a rational and optimal solution. Most real-world problems, however, are characterized by uncertainty, the need to consider
an enormous number of variables and possible courses of action at each stage in solving the problem, and the need to optimize the solution subject to multiple interacting
constraints. There are reliable individual differences in people’s abilities to solve such realistic problems. It also seems likely that people’s ability to solve these difficult problems reflects, or depends on, their intelligence. We report on a study of N = 101 adults
who completed a series of visual optimization problems (Traveling Salesperson, Minimum Spanning Tree, and Generalized Steiner Tree Problems), as well as a cognitive
optimization problem (a version of the Secretary Problem). We also characterized these individuals along three relevant and important cognitive abilities dimensions--fluid ability, visuo-spatial ability, and cognitive processing speed. Modeling of covariance structures indicated that performance on both types of optimization problems relies on general intelligence and raises the possibility that they can be used to assess intelligence.
1
https://docs.lib.purdue.edu/jps/vol1/iss1/3
oai:docs.lib.purdue.edu:jps-1004
2006-12-05T20:19:54Z
publication:jps
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Human Performance on Visually Presented Traveling Salesperson Problems with Varying Numbers of Nodes
Dry, Matthew
Lee, Michael D.
Vickers, Douglas
Hughes, Peter
Article
We investigated the properties of the distribution of human solution times for Traveling Salesperson Problems (TSPs) with increasing numbers of nodes. New experimental data are presented that measure solution times for carefully chosen representative problems with 10, 20, . . . 120 nodes. We compared the solution times predicted by the convex hull procedure proposed by MacGregor and Ormerod (1996), the hierarchical approach of
Graham, Joshi, and Pizlo (2000), and by five algorithms drawn from the artificial intelligence and operations research literature. The most likely polynomial model for describing the relationship between mean solution time and the size of a TSP is linear or near-linear over the range of problem sizes tested, supporting the earlier finding of Graham et al. (2000). We argue the properties of the solution time distributions place strong constraints on the development of detailed models of human performance for TSPs, and provide some evaluation of previously proposed models in light of our findings.
1
https://docs.lib.purdue.edu/jps/vol1/iss1/4
oai:docs.lib.purdue.edu:jps-1005
2006-12-05T20:27:48Z
publication:jps
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A Comparison of Heuristic and Human Performance on Open Versions of the Traveling Salesperson Problem
MacGregor, James N.
Chronicle, Edward P.
Ormerod, Thomas C.
Article
We compared the performance of three heuristics with that of subjects on variants of a well-known combinatorial optimization task, the Traveling Salesperson Problem (TSP). The present task consisted of finding the shortest path through an array of points from one side of the array to the other. Like the standard TSP, the task is computationally intractable and, as with the standard TSP, people appear to be able to find good solutions with relative ease. The three heuristics used mechanisms that have been cited as potentially relevant in human performance in the standard task. These were: convex hull, nearest neighbor, and crossing avoidance. We compared heuristic and human performance in terms of lengths of paths, overlap between solutions, and number of crossings. Of the three heuristics, the convex hull appeared to result in the best overall fit withhuman solutions.
1
https://docs.lib.purdue.edu/jps/vol1/iss1/5
oai:docs.lib.purdue.edu:jps-1006
2006-12-05T20:31:46Z
publication:jps
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Perceptual or Analytical Processing? Evidence from Children's and Adult's Performance on the Euclidean Traveling Salesperson Problem
van Rooij, Iris
Schactman, Alissa
Kadlec, Helena
Stege, Ulrike
Article
The Euclidean Traveling Salesperson Problem (E-TSP) is a useful task to study how humans optimize when faced with computational intractability. It has been found that humans are capable of finding high-quality solutions for E TSP in a relatively short time and with seemingly little cognitive effort. This observation has led to two general proposals: The high quality of performance on E-TSP reflects (a) the output of automatic and innate perceptual processes or (b) a fundamentally intelligent approach to the task by humans. An experiment was performed to compare performance of three age groups (7- year-olds, 12-year-olds, and adults). Our findings provide corroborating evidence that high-level performance on E-TSP is attainable with perceptual processing alone. At the same time, the exceptionally high performance of adult participants suggests that they additionally exploit their cognitive-analytic skills to improve upon what their visual systems provide.
1
https://docs.lib.purdue.edu/jps/vol1/iss1/6
oai:docs.lib.purdue.edu:jps-1007
2013-04-19T22:21:12Z
publication:jps
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Contents
Article
1
https://docs.lib.purdue.edu/jps/vol1/iss1/1
oai:docs.lib.purdue.edu:jps-1008
2006-12-08T20:57:24Z
publication:jps
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Editor's Introduction
Pizlo, Zygmunt
Article
1
https://docs.lib.purdue.edu/jps/vol1/iss1/2
oai:docs.lib.purdue.edu:jps-1009
2006-12-13T21:37:00Z
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Traveling Salesman Problem: A Foveating Pyramid Model
Pizlo, Zygmunt
Stefanov, Emil
Saalweachter, John
Li, Zheng
Haxhimusa, Yll
Kropatsch, Walter G.
Article
We tested human performance on the Euclidean Traveling Salesman Problem using problems with 6–50 cities. Results confirmed our earlier findings that: (a) the time of solving a problem is proportional to the number of cities, and (b) the solution error grows very slowly with the number of cities. We formulated a new version of a pyramid
model. The new model has an adaptive spatial structure, and it simulates visual acuity and visual attention. Specifically, the model solves the E-TSP problem sequentially by moving attention from city to city, the same way human subjects do. The model includes a parameter representing the magnitude of local search. This parameter allows modeling individual differences among the subjects. The computational complexity of the current implementation of the model is O(n2), but this can most likely be improved to O[nlog(n)]. Simulation experiments demonstrated psychological plausibility of the new model.
1
https://docs.lib.purdue.edu/jps/vol1/iss1/8
oai:docs.lib.purdue.edu:jps-1010
2007-06-19T15:07:54Z
publication:jps
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Theory Driven Hints in the Cheap Necklace Problem: A Preliminary Investigation
Chu, Yun
Dewald, Andrew D.
Chronicle, Edward P.
Insight
hints
heuristics
maximization
representational change
Article
Three experiments investigated the effects of two hints derived from the Criterion for Satisfactory Progress theory (CSP) and Representational Change Theory (RCT) on the cheap necklace problem (insight problem). In Experiment 1, fewer participants given the CSP hint used an incorrect (maximizing) first move than participants given the RCT hint or control participants given no hint on a single attempt at the problem. Experiment 2 found the number of trials to solution was fewer in the CSP condition than in the control over ten trials, and there were fewer incorrect first moves in the CSP. The results appear to support the CSP theory. However, in Experiment 3, the CSP and RCT hints were combined yielding a 75% solution rate over 34.88% in the control. Perhaps aspects from both theories are employed during the problem solving process.
1
https://docs.lib.purdue.edu/jps/vol1/iss2/4
oai:docs.lib.purdue.edu:jps-1012
2007-06-29T20:28:44Z
publication:jps
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Group Decision-Making on an Optimal Stopping Problem
Lee, Michael D
Paradowski, Michael J
optimal stopping
decision-making
group decision-making
Article
We consider group decision-making on an optimal stopping problem, for which large and stable individual differences have previously been established. In the problem, people are presented with a sequence of five random numbers between 0 and 100, one at a time, and are required to choose the maximum of the sequence, without being allowed to return to earlier values in the sequence. We examine group decision-making on these problems in an experimental setting where group members are isolated from one another, and interact solely via networked computers. The group members register their initial accept or reject decision for each value in the sequence, and then providing a potentially revised decision having viewed the recommendations of the other group members. Group decisions are made according to one of three conditions, requiring either consensus to accept from all group members, a majority of accept decisions from the group, or the acceptance of an appointed group leader. We compare individual decision-making to group decision-making under these three conditions, and find that, under some conditions, groups often significantly outperform even their best members. Using a signal detection analysis we provide an account of how the group decision-making conditions differ from one another, and from individual decision-making. Key findings are that people do not often revise their decisions, but, in the consensus and leadership conditions, are more conservative in their initial decisions. This conservatism removes the individual bias towards choosing values too early in the sequence, allowing the groups to perform better than their individual members. In the majority condition, however, people continue to behave as they did individually, and the group shows the same bias in decision-making.
1
https://docs.lib.purdue.edu/jps/vol1/iss2/06
oai:docs.lib.purdue.edu:jps-1015
2007-06-19T15:05:45Z
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In Memoriam: Dr. Edward P. Chronicle
MacGregor, James
Ormerod, Thomas
Article
1
https://docs.lib.purdue.edu/jps/vol1/iss2/1
oai:docs.lib.purdue.edu:jps-1014
2009-03-03T20:12:45Z
publication:jps
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Contents
Article
1
https://docs.lib.purdue.edu/jps/vol1/iss2/2
oai:docs.lib.purdue.edu:jps-1016
2007-06-19T15:07:09Z
publication:jps
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Human Problem Solving in 2006
Pizlo, Zygmunt
Article
This paper presents a bibliography of a little more than 100 references related to human problem solving, arranged by subject matter. The references were taken from PsycInfo and Compendex databases. Only journal papers, books and dissertations are included. The topics include human development, education, neuroscience, research in applied settings, as well as animal studies. A few references from artificial intelligence are also given.
1
https://docs.lib.purdue.edu/jps/vol1/iss2/3
oai:docs.lib.purdue.edu:jps-1029
2008-07-24T13:20:30Z
publication:jps
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publication:libraries
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Seeing is as Good as Doing
Osman, Magda
Article
Given the privileged status claimed for active learning in a variety of domains (visuomotor
learning, causal induction, problem solving, education, skill learning), the present study
examines whether action-based learning is a necessary, or a suffi cient, means of acquiring
the relevant skills needed to perform a task typically described as requiring active
learning. To achieve this, the present study compares the effects of action-based and
observation-based learning when controlling a complex dynamic task environment (N =
96). Both action- and observation-based individuals learn either by describing the changes
in the environment in the form of a conditional statement, or not. The study reveals that
for both active and observational learners, advantages in performance (p < .05), accuracy
in knowledge of the task (p < .05), and self-insight (p < .05) are found when learning is
based on inducing rules from the task environment. Moreover, the study provides evidence
suggesting that, given task instructions that encourage rule-based knowledge, both active
and observation-based learning can lead to high levels of problem solving skills in a
complex dynamic environment.
1
https://docs.lib.purdue.edu/jps/vol2/iss1/3
oai:docs.lib.purdue.edu:jps-1027
2009-05-05T17:28:27Z
publication:jps
publication:librariespublishing
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Contents
Article
1
https://docs.lib.purdue.edu/jps/vol2/iss1/1
oai:docs.lib.purdue.edu:jps-1030
2008-07-24T13:19:26Z
publication:jps
publication:librariespublishing
publication:libraries
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Individual Differences in Optimization Problem Solving: Reconciling Conflicting Results
Chronicle, Edward P.
MacGregor, James N.
Lee, Michael
Ormerod, Thomas C.
Hughes, Peter
Article
Results on human performance on the Traveling Salesman Problem (TSP) from different laboratories show high consistency. However, one exception is in the area of individual differences. While one research group has consistently failed to find systematic individual differences across instances of TSPs (Chronicle, MacGregor and Ormerod), another group (Vickers, Lee and associates) has found individual differences both within TSP performance and between TSP performance and other cognitive tasks. Among possible reasons for the conflicting results are differences in procedure and differences in the problem instances used. To try to resolve the discrepancy, we collected data on TSP performance by combining the procedure used by one group with problem instances used by the other. The comparison involved nine 30-node and nine 40-node TSP problems previously used by the Vickers group, using computer presentation. Here, we had the same problems completed by 112 participants using a paper-and-pencil mode of presentation. We examined the results in the form of distributions of correlations across individuals for each pair of problems of the same size. The distributions for the computer and paper forms of presentation were very similar, and centered between correlations of 0.20 and 0.30. The results indicated the presence of individual differences at a level that fell between those previously reported by the two laboratories. The pattern of results indicated that previous discrepancies did not arise because of differences in procedure. Instead, individual differences appeared to become more prevalent as the difficulty of problems increased. The results are consistent with an explanation that performance on simpler instances is dominated by lower-level processes, but that as instance difficulty increases, higher-level functions become increasingly involved.
1
https://docs.lib.purdue.edu/jps/vol2/iss1/4
oai:docs.lib.purdue.edu:jps-1028
2008-07-24T13:23:01Z
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Some Tours are More Equal than Others: The Convex-Hull Model Revisited with Lessons for Testing Models of the Traveling Salesperson Problem
Tak, Susanne
Plaisier, Marco
van Rooij, Iris
Article
To explain human performance on the Traveling Salesperson problem (TSP), MacGregor,
Ormerod, and Chronicle (2000) proposed that humans construct solutions according to the
steps described by their convex-hull algorithm. Focusing on tour length as the dependent
variable, and using only random or semirandom point sets, the authors claimed empirical
support for their model. In this paper we argue that the empirical tests performed by
MacGregor et al. do not constitute support for the model, because they instantiate what
Meehl (1997) coined "weak tests" (i.e., tests with a high probability of yielding confi rmation
even if the model is false). To perform "strong" tests of the model, we implemented
the algorithm in a computer program and compared its performance to that of humans
on six point sets. The comparison reveals substantial and systematic differences in the
shapes of the tours produced by the algorithm and human participants, for fi ve of the
six point sets. The methodological lesson for testing TSP models is twofold: (1) Include
qualitative measures (such as tour shape) as a dependent variable, and (2) use point sets
for which the model makes “risky” predictions.
1
https://docs.lib.purdue.edu/jps/vol2/iss1/2
oai:docs.lib.purdue.edu:jps-1042
2009-05-01T13:45:21Z
publication:jps
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Human Problem Solving in 2008
Pizlo, Zygmunt
Article
This paper presents a bibliography of more than 200 references related to human problem solving, arranged by subject matter. The references were taken from PsycInfo database. Journal papers, book chapters, books and dissertations are included. The topics include human development, education, neuroscience, research in applied settings, as well as animal studies.
1
https://docs.lib.purdue.edu/jps/vol2/iss1/5
oai:docs.lib.purdue.edu:jps-1043
2009-05-11T16:36:39Z
publication:jps
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The Self-Organization of Insight: Entropy and Power Laws in Problem Solving
Stephen, Damian G.
Dixon, James A.
Article
Explaining emergent structure remains a challenge for all areas of cognitive science, and problem solving is no exception. The modern study of insight has drawn attention to the issue of emergent cognitive structure in problem solving research. We propose that the explanation of insight is beyond the scope of conventional approaches to cognitive science in terms of symbolic representation. Cognition may be better described in
terms of an open, nonlinear dynamical system. By this reasoning, insight would be the self-organization of novel structure. Self-organization is a well-studied phenomenon
of dynamical systems theory, associated with specific trends in entropy and power-law behavior. We present work using nonlinear dynamics to capture these trends in entropy and power-law behavior and thus to predict the self-organization of novel cognitive structure in a problem-solving task. Future explorations of problem solving will benefit from considerations of the continuous nonlinear interactions among action, cognition, and the environment.
1
https://docs.lib.purdue.edu/jps/vol2/iss1/6
oai:docs.lib.purdue.edu:jps-1054
2010-01-06T14:56:59Z
publication:jps
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Contents
Article
1
https://docs.lib.purdue.edu/jps/vol2/iss2/1
oai:docs.lib.purdue.edu:jps-1055
2010-01-06T14:57:45Z
publication:jps
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New Perspectives on Human Problem Solving
Goldstone, Robert L.
Pizlo, Zygmunt
Article
1
https://docs.lib.purdue.edu/jps/vol2/iss2/2
oai:docs.lib.purdue.edu:jps-1056
2010-01-06T14:58:11Z
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Obstacles in Investigating the Role of Restructuring in Insightful Problem Solving
Ash, Ivan K.
Cushen, Patrick J.
Wiley, Jennifer
insight
problem solving
creativity
Article
In the present article, we articulate three assumptions underlying theories proposing that restructuring processes play a key role in insightful problem solving: representational difficulty, representational change, and discontinuity in solution processes. We argue that these assumptions need empirical validation to justify the proposition of restructuring mechanisms that are unique from those involved in classic information-processing theories of problem solving. To this end, we review some theoretical and methodological obstacles that are inherent in the investigation of the existence and nature of restructuring processes. We then offer some recommendations on how to overcome or avoid these obstacles in future studies. Finally, we discuss some questions to help motivate new research.
1
https://docs.lib.purdue.edu/jps/vol2/iss2/3
oai:docs.lib.purdue.edu:jps-1061
2010-01-06T14:59:58Z
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Examining the Role of Manipulatives and Metacognition on Engagement, Learning, and Transfer
Belenky, Daniel M.
Nokes, Timothy J.
learning
engagement
transfer
problem solving
manipulatives
metacognition
Article
How does the type of learning material impact what is learned? The current research investigates
the nature of students’ learning of math concepts when using manipulatives
(Uttal, Scudder, & DeLoache, 1997). We examined how the type of manipulative (concrete,
abstract, none) and problem-solving prompt (metacognitive or problem-focused) affect
student learning, engagement, and knowledge transfer. Students who were given concrete
manipulatives with metacognitive prompts showed better transfer of a procedural skill
than students given abstract manipulatives or those given concrete manipulatives with
problem-focused prompts. Overall, students who reported low levels of engagement
showed better learning and transfer when getting metacognitive prompts, whereas
students who reported high levels of engagement showed better learning and transfer
when getting the problem-focused prompts. The results are discussed in regards to their
implications for education and instruction.
1
https://docs.lib.purdue.edu/jps/vol2/iss2/6
oai:docs.lib.purdue.edu:jps-1057
2010-01-06T14:58:37Z
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Causal Induction from Continuous Event Streams: Evidence for Delay-Induced Attribution Shifts
Buehner, Marc J.
May, Jon
causality
reasoning
time perception
continuity
induction
associative learning
Article
Contemporary theories of Human Causal Induction assume that causal knowledge is
inferred from observable contingencies. While this assumption is well supported by empirical
results, it fails to consider an important problem-solving aspect of causal induction
in real time: In the absence of well structured learning trials, it is not clear whether the
effect of interest occurred because of the cause under investigation, or on its own accord.
Attributing the effect to either the cause of interest or alternative background causes is an
important precursor to induction. We present a new paradigm based on the presentation
of continuous event streams, and use it to test the Attribution-Shift Hypothesis (Shanks &
Dickinson, 1987), according to which temporal delays sever the attributional link between
cause and effect. Delays generally impaired attribution to the candidate, and increased
attribution to the constant background of alternative causes. In line with earlier research
(Buehner & May, 2002, 2003, 2004) prior knowledge and experience mediated this effect.
Pre-exposure to a causally ineffective background context was found to facilitate
the discovery of delayed causal relationships by reducing the tendency for attributional
shifts to occur. However, longer exposure to a delayed causal relationship did not improve
discovery. This complex pattern of results is problematic for associative learning theories,
but supports the Attribution-Shift Hypothesis.
1
https://docs.lib.purdue.edu/jps/vol2/iss2/4
oai:docs.lib.purdue.edu:jps-1060
2010-01-06T14:59:22Z
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Modeling Human Performance in Restless Bandits with Particle Filters
Yi, Michael S.K.
Steyvers, Mark
Lee, Michael
restless bandits
reinforcement learning
sequential decision-making
change detection
non-stationary environments
Article
Bandit problems provide an interesting and widely-used setting for the study of sequential
decision-making. In their most basic form, bandit problems require people to choose
repeatedly between a small number of alternatives, each of which has an unknown rate
of providing reward. We investigate restless bandit problems, where the distributions of
reward rates for the alternatives change over time. This dynamic environment encourages
the decision-maker to cycle between states of exploration and exploitation. In one environment
we consider, the changes occur at discrete, but hidden, time points. In a second
environment, changes occur gradually across time. Decision data were collected from
people in each environment. Individuals varied substantially in overall performance and
the degree to which they switched between alternatives. We modeled human performance
in the restless bandit tasks with two particle filter models: one that can approximate the
optimal solution to a discrete restless bandit problem, and another simpler particle filter
that is more psychologically plausible. It was found that the simple particle filter was able
to account for most of the individual differences.
1
https://docs.lib.purdue.edu/jps/vol2/iss2/5
oai:docs.lib.purdue.edu:jps-1063
2010-01-06T15:00:44Z
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The Paradigm Recursion: Is It More Accessible When Introduced in Middle School?
Gunion, Katherine
Milford, Todd
Stege, Ulrike
recursion
computer science education
kineasthetic learning activities
Article
Recursion is a programming paradigm as well as a problem solving strategy thought to be
very challenging to grasp for university students. This article outlines a pilot study, which
expands the age range of students exposed to the concept of recursion in computer science
through instruction in a series of interesting and engaging activities. In this study,
a small number of students (n = 9) aged 11 to 13 years, were presented with a new and
unique recursion curriculum involving hands-on experiences over a seven-week period
at the University of Victoria, Canada. The curriculum was comprised of a series of progressively
challenging recursion activities—roughly based upon the ideas of ‘Computer Science
Unplugged’ (Bell, Witten, & Fellows, 2009)—and included programming applications with
MicroWorlds EX, a programming language based on LOGO. Through this engagement,
an increased number of students recognized and understood the concepts covered. We
hypothesize that through experiences for youth with activities such as those outlined
here, the number of students who understand fundamental computer science applications
and who might potentially pursue computer science in post-secondary education
will increase. We hypothesis further that through an earlier encounter of “challenging”
concepts the learning and understanding of those will become easier at the university
level. In this paper, the curriculum, classroom experiences, preliminary, largely descriptive
and qualitative results and next steps in the research are discussed.
1
https://docs.lib.purdue.edu/jps/vol2/iss2/8
oai:docs.lib.purdue.edu:jps-1062
2010-01-06T15:00:21Z
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The Effects of Number and Level of Restructuring in Insight Problem Solving
MacGregor, James N.
Cunningham, John B.
insight problem solving
rebus puzzles
Article
Insight problem solving is characterized by restructuring. We hypothesized that the difficulty
of rebus puzzles could be manipulated by systematically varying the restructurings
required to solve them. An experiment using rebus puzzles varied the number of restructurings
(one or two) required to solve a problem and the level at which the restructuring
took place (sub-word level, word level, and supra-word level). Solution rates were higher
for one restructuring than two, and higher for restructuring at the supra-word level (relation
between words) than at lower levels. To explain the findings, we suggest that rebus
puzzles initially engage normal reading processes, which involve extracting meaning at
the level of relations between words.
1
https://docs.lib.purdue.edu/jps/vol2/iss2/7
oai:docs.lib.purdue.edu:jps-1076
2010-10-06T14:15:02Z
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publication:pupoaj
The Effect of Strategy on Problem Solving: An fMRI Study
Newman, Sharlene D.
Pruce, Benjamin
Rusia, Akash
Burns, Thomas, Jr.
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss1/2
oai:docs.lib.purdue.edu:jps-1078
2010-10-06T14:17:43Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Heuristics in Problem Solving: The Role of Direction in Controlling Search Space
Chu, Yun
Li, Zheng
Su, Yong
Pizlo, Zygmunt
Heuristics in Problem Solving
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss1/3
oai:docs.lib.purdue.edu:jps-1080
2010-10-06T14:20:46Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Minimal Paths in the City Block: Human Performance on Euclidean and Non-Euclidean Traveling Salesperson Problems
Walwyn, Amy L.
Navarro, Daniel J.
Minimal Paths in the City Block
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss1/5
oai:docs.lib.purdue.edu:jps-1081
2010-10-06T14:22:27Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Causality in Solving Economic Problems
Robinson, A. Emanuel
Sloman, Steven A.
Hagmayer, York
Hertzog, Christopher K.
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss1/6
oai:docs.lib.purdue.edu:jps-1079
2010-10-06T14:19:24Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
When Do Words Promote Analogical Transfer?
Son, Ji Y.
Doumas, Leonidas A. A.
Goldstone, Robert L.
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss1/4
oai:docs.lib.purdue.edu:jps-1077
2010-10-06T14:15:38Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Contents
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss1/1
oai:docs.lib.purdue.edu:jps-1090
2011-03-04T15:16:12Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Human Performance on the Traveling Salesman and Related Problems: A Review
MacGregor, James N.
Chu, Yun
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss2/2
oai:docs.lib.purdue.edu:jps-1092
2011-03-04T15:17:06Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Finite Optimal Stopping Problems: The Seller’s Perspective
Hemmati, Mehdi
Smith, J. Cole
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss2/4
oai:docs.lib.purdue.edu:jps-1091
2011-03-04T15:16:40Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
What Does (and Doesn’t) Make Analogical Problem Solving Easy? A Complexity-Theoretic Perspective
Wareham, Todd
Evans, Patricia
Rooij, Iris van
What Does (and Doesn’t) Make Analogical Problem Solving Easy?
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss2/3
oai:docs.lib.purdue.edu:jps-1095
2011-03-04T15:19:34Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
The Minimal Control Principle Predicts Strategy Shifts in the Abstract Decision Making Task
Taatgen, Niels A.
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss2/7
oai:docs.lib.purdue.edu:jps-1093
2011-03-04T15:17:29Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Quality, Conformity, and Conflict: Questioning the Assumptions of Osborn’s Brainstorming Technique
Goldenberg, Olga
Wiley, Jennifer
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss2/5
oai:docs.lib.purdue.edu:jps-1096
2011-03-04T15:19:59Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
2D and 3D Traveling Salesman Problem
Haxhimusa, Yll
Carpenter, Edward
Catrambone, Joseph
Foldes, David
Stefanov, Emil
Arns, Laura
Pizlo, Zygmunt
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss2/8
oai:docs.lib.purdue.edu:jps-1089
2011-03-04T15:15:40Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Contents
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss2/1
oai:docs.lib.purdue.edu:jps-1094
2011-03-04T15:19:01Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Human Performance on Insight Problem Solving: A Review
Chu, Yun
MacGregor, James N.
Article
1
https://docs.lib.purdue.edu/jps/vol3/iss2/6
oai:docs.lib.purdue.edu:jps-1116
2012-02-23T19:21:21Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Contents
Article
1
https://docs.lib.purdue.edu/jps/vol4/iss1/1
oai:docs.lib.purdue.edu:jps-1119
2012-02-23T19:22:55Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Book Review of Rosenhouse, The Monty Hall Problem
Burkholder, Leslie
Article
1
https://docs.lib.purdue.edu/jps/vol4/iss1/4
oai:docs.lib.purdue.edu:jps-1118
2012-02-23T19:22:26Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
The Process of Solving Complex Problems
Fischer, Andreas
Greiff, Samuel
Funke, Joachim
Complex Problem Solving
CPS
Operative Intelligence
Dynamic Problem Solving
Dynamic Decision Making
Expertise
Article
<p>This article is about Complex Problem Solving (CPS), its history in a variety of research domains (e.g., human problem solving, expertise, decision making, and intelligence), a formal definition and a process theory of CPS applicable to the interdisciplinary field. CPS is portrayed as (a) knowledge acquisition and (b) knowledge application concerning the goal-oriented control of systems that contain many highly interrelated elements (i.e., complex systems). The impact of implicit and explicit knowledge as well as systematic strategy selection on the solution process are discussed, emphasizing the importance of (1) information generation (due to the initial intransparency of the situation), (2) information reduction (due to the overcharging complexity of the problem’s structure), (3) model building (due to the interconnectedness of the variables), (4) dynamic decision making (due to the eigendynamics of the system), and (5) evaluation (due to many, interfering and/or ill-defined goals).</p>
1
https://docs.lib.purdue.edu/jps/vol4/iss1/3
oai:docs.lib.purdue.edu:jps-1117
2012-02-23T19:21:52Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Clustering, Randomness, and Regularity: Spatial Distributions and Human Performance on the Traveling Salesperson Problem and Minimum Spanning Tree Problem
Dry, Matthew
Preiss, Kym
Wagemans, Johan
problem solving
optimization
visual perception
Article
<p>We investigated human performance on the Euclidean Traveling Salesperson Problem (TSP) and Euclidean Minimum Spanning Tree Problem (MST-P) in regards to a factor that has previously received little attention within the literature: the spatial distributions of TSP and MST-P stimuli. First, we describe a method for quantifying the relative degree of clustering, randomness or regularity within point distributions. We then review evidence suggesting this factor might influence human performance on the two problem types. Following this we report an experiment in which the participants were asked to solve TSP and MST-P test stimuli that had been generated to be either highly clustered, random, or highly regular. The results indicate that for both the TSP and MST-P the participants tended to produce better quality solutions when the stimuli were highly clustered compared to random, and similarly, better quality solutions for random compared to highly regular stimuli. It is suggested that these results provide support for the ideas that human solvers attend to salient clusters of nodes when solving these problems, and that a similar process (or series of processes) may underlie human performance on these two tasks.</p>
1
https://docs.lib.purdue.edu/jps/vol4/iss1/2
oai:docs.lib.purdue.edu:jps-1120
2012-02-23T19:23:49Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Human Problem Solving in 2010
Pizlo, Zygmunt
Article
<p>This paper presents a bibliography of 100 references related to human problem solving, arranged by subject matter. The references were taken from PsycInfo database. Journal papers, book chapters, and dissertations are included. The topics include human development, education, neuroscience, and research in applied settings, as well as animal studies.</p>
1
https://docs.lib.purdue.edu/jps/vol4/iss1/5
oai:docs.lib.purdue.edu:jps-1122
2012-05-12T03:04:27Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Contents
Article
1
https://docs.lib.purdue.edu/jps/vol4/iss2/1
oai:docs.lib.purdue.edu:jps-1125
2012-05-12T03:11:37Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Testing the Cue Dependence of Problem-Solving-Induced Forgetting
Storm, Benjamin C.
Koppel, Rebecca H.
problem solving
memory
forgetting
retrieval-induced forgetting
cue independence
fixation
Article
<p>Thinking and remembering can cause forgetting. In the context of remembering, retrieving one item can cause the forgetting of other items (Anderson, Bjork, & Bjork, 1994). A similar phenomenon has been observed in the context of creative problem solving—attempting to generate a target associate in the Remote Associates Test (RAT) can cause the forgetting of inappropriate associates (Storm, Angello, & Bjork, 2011). Experiment 1 examined whether this problem-solving-induced forgetting is cue dependent or cue independent by manipulating the cues used at final test. Whereas some participants were tested on the inappropriate associates using the same cues that were used during problem solving, other participants were tested using new, or independent, cues. Problem-solving-induced forgetting was observed in the same-cue condition, but not in the new-cue condition. Experiment 2 replicated the overall absence of problem-solvinginduced forgetting in the new-cue condition and found that individual differences in cue-independent forgetting did not predict problem-solving performance on a separate set of RAT problems.</p>
1
https://docs.lib.purdue.edu/jps/vol4/iss2/4
oai:docs.lib.purdue.edu:jps-1128
2012-05-12T03:21:40Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Firing the Executive: When an Analytic Approach to Problem Solving Helps and Hurts
Aiello, Daniel A.
Jarosz, Andrew F.
Cushen, Patrick J.
Wiley, Jennifer
intuition
creativity
bilingual
Article
<p>There is a general assumption that a more controlled or more focused attentional state is beneficial for most cognitive tasks. However, there has been a growing realization that creative problem solving tasks, such as the Remote Associates Task (RAT), may benefit from a less controlled solution approach. To test this hypothesis, in a 2x2 design, we manipulated whether solvers were given the RAT before or after an implicit learning task. We also varied whether they were told to “use their gut” as part of either initial task. The results suggest that a less analytic approach engendered by a “use your gut” instruction benefits performance on the RAT for monolingual solvers. The same benefit was not found for bilingual speakers suggesting that more controlled solution processes may be needed when speakers with multiple lexicons perform this task, which relies heavily on accessing common phrases in a particular language.</p>
1
https://docs.lib.purdue.edu/jps/vol4/iss2/7
oai:docs.lib.purdue.edu:jps-1124
2012-05-12T03:10:06Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Clue Insensitivity in Remote Associates Test Problem Solving
Smith, Steven M.
Sifonis, Cynthia M.
Angello, Genna
remote
associates
incubation
hint
Article
<p>Does spreading activation from incidentally encountered hints cause incubation effects? We used Remote Associates Test (RAT) problems to examine effects of incidental clues on impasse resolution. When solution words were seen incidentally 3-sec before initially unsolved problems were retested, more problems were resolved (Experiment 1). When strong semantic associates of solutions were used as incidental clues, however, it did not improve resolution (Experiments 2 and 4). The semantic associates we used as incidental clues primed our RAT solution words in a lexical decision task, but they did not facilitate impasse resolution unless participants were explicitly instructed to use the associates as hints to the retested problems (Experiment 4). The results do not support the theory that spreading activation is a sufficient cause of incubation effects, and suggest that serendipitously encountered clues (i.e., words that are semantically related to RAT solutions) have no automatic benefit on impasse resolution in RAT problem solving.</p>
1
https://docs.lib.purdue.edu/jps/vol4/iss2/3
oai:docs.lib.purdue.edu:jps-1129
2012-05-12T03:23:10Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Is Insight Always the Same? A Protocol Analysis of Insight in Compound Remote Associate Problems
Cranford, Edward A.
Moss, Jarrod
Article
<p>Compound Remote Associate (CRA) problems have been used to investigate insight problem solving using both behavioral and neuroimaging techniques. However, it is unclear to what extent CRA problems exhibit characteristics of insight such as impasses and restructuring. CRA problem-solving characteristics were examined in a study in which participants solved CRA problems while providing concurrent verbal protocols. The results show that solutions subjectively judged as insight by participants do exhibit some characteristics of insight. However, the results also show that there are at least two different ways in which people experience insight when solving CRA problems. Sometimes problems are solved and judged as insight when the solution is the first thing considered, but these solutions do not exhibit any characteristics of insight aside from the “Aha!” experience. In other cases, the solution is derived after a longer period of problem solving, and the solution process more closely resembles insight as it is has been traditionally defined in the literature. The results show that separating these two types of solution processes may provide a better understanding of the behavioral and neuroanatomical correlates of insight solutions.</p>
1
https://docs.lib.purdue.edu/jps/vol4/iss2/8
oai:docs.lib.purdue.edu:jps-1123
2012-05-12T03:07:34Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Investigating Insight as Sudden Learning
Ash, Ivan K.
Jee, Benjamin D.
Wiley, Jennifer
insight
learning
impasse
problem solving
Article
<p>Gestalt psychologists proposed two distinct learning mechanisms. Associative learning occurs gradually through the repeated co-occurrence of external stimuli or memories. Insight learning occurs suddenly when people discover new relationships within their prior knowledge as a result of reasoning or problem solving processes that re-organize or restructure that knowledge. While there has been a considerable amount of research on the type of problem solving processes described by the Gestalt psychologists, less has focused on the learning that results from these processes. This paper begins with a historical review of the Gestalt theory of insight learning. Next, the core assumptions of Gestalt insight learning theory are empirically tested with a study that investigated the relationships among problem difficulty, impasse, initial problem representations, and resolution effects. Finally, Gestalt insight learning theory is discussed in relation to modern information processing theories of comprehension and memory formation.</p>
1
https://docs.lib.purdue.edu/jps/vol4/iss2/2
oai:docs.lib.purdue.edu:jps-1127
2012-05-24T12:23:13Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Visual Attention Modulates Insight Versus Analytic Solving of Verbal Problems
Wegbreit, Ezra
Suzuki, Satoru
Grabowecky, Marcia
Kounios, John
Beeman, Mark
verbal problem solving
visual attention
insight
creativity
focused attention
broadened attention
Article
<p>Behavioral and neuroimaging findings indicate that distinct cognitive and neural processes underlie solving problems with sudden insight. Moreover, people with less focused attention sometimes perform better on tests of insight and creative problem solving. However, it remains unclear whether different states of attention, within individuals, influence the likelihood of solving problems with insight or with analysis. In this experiment, participants (N = 40) performed a baseline block of verbal problems, then performed one of two visual tasks, each emphasizing a distinct aspect of visual attention, followed by a second block of verbal problems to assess change in performance. After participants engaged in a center-focused flanker task requiring relatively focused visual attention, they reported solving more verbal problems with analytic processing. In contrast, after participants engaged in a rapid object identification task requiring attention to broad space and weak associations, they reported solving more verbal problems with insight. These results suggest that general attention mechanisms influence both visual attention task performance and verbal problem solving.</p>
1
https://docs.lib.purdue.edu/jps/vol4/iss2/6
oai:docs.lib.purdue.edu:jps-1126
2012-05-12T03:15:50Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Remote Associates Test and Alpha Brain Waves
Haarmann, Henk J.
George, Timothy
Smaliy, Alexei
Dien, Joseph
Remote Associates Test
Alpha brain waves
EEG neurofeedback
problem incubation
Article
<p>Previous studies found that performance on the remote associates test (RAT) improves after a period of incubation and that increased alpha brain waves over the right posterior brain predict the emergence of RAT insight solutions. We report an experiment that tested whether increased alpha brain waves during incubation improve RAT performance. Participants received two blocks of RAT items (RAT1 and RAT2), with the second block consisting of items that were not solved during the first block. Participants were randomly assigned to three groups, which were matched for their number of RAT1 solutions. Participants in an alpha-up neurofeedback group aimed to increase their alpha brain waves over the right posterior brain in between the two blocks, whereas participants in an alpha-down neurofeedback group aimed to decrease these same brain waves. A third group of participants did not perform neurofeedback and proceeded immediately from the first to the second block of RAT items. We found evidence for more RAT2 solutions in participants who interrupted their RAT performance with neurofeedback, especially in ones who showed high alpha brain waves during neurofeedback. These results are consistent with the notion that an alert but relaxed mental state, indexed by alpha brain waves, may aid the read out of an implicitly activated memory network of weak associates.</p>
1
https://docs.lib.purdue.edu/jps/vol4/iss2/5
oai:docs.lib.purdue.edu:jps-1130
2012-05-12T03:24:43Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Intuitive Tip of the Tongue Judgments Predict Subsequent Problem Solving One Day Later
Collier, Azurii K.
Beeman, Mark
insight
problem solving
intuition
Article
<p>Often when failing to solve problems, individuals report some idea of the solution, but cannot explicitly access the idea. We investigated whether such intuition would relate to improvements in solving and to the manner in which a problem was solved after a 24- hour delay. On Day 1, participants attempted to solve Compound Remote Associate problems, for which they viewed three problem words (crab, sauce, pine) and tried to generate one solution word (apple) that could form a compound word with each problem word (crabapple, applesauce, pineapple). For problems they failed to solve, participants reported whether they had an intuitive sense that they might have solution related processing in the back of their mind, similar to a Tip-of-the-Tongue (TOT) experience. After an overnight delay, on Day 2 participants attempted to solve unsolved Old problems from Day 1 (mixed among New problems). Participants solved more Old problems for which they reported a TOT on Day 1 than Old problems without a TOT, demonstrating a TOT specific incubation effect. Interestingly, participants reported solving a marginally higher proportion of these TOT problems, compared to No TOT problems, with insight. Results suggest that intuitive TOT judgments are indicative of subthreshold solution related activation that can facilitate eventual problem solving, especially with insight.</p>
1
https://docs.lib.purdue.edu/jps/vol4/iss2/9
oai:docs.lib.purdue.edu:jps-1131
2013-10-10T19:52:41Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Introspection in Problem Solving
Jäkel, Frank
Schreiber, Cornell
introspection
problem solving
metacognition
verbal reports
think aloud
Article
<p>Problem solving research has encountered an impasse. Since the seminal work of Newell und Simon (1972) researchers do not seem to have made much theoretical progress (Batchelder and Alexander, 2012; Ohlsson, 2012). In this paper we argue that one factor that is holding back the field is the widespread rejection of introspection among cognitive scientists. We review evidence that introspection improves problem solving performance, sometimes dramatically. Several studies suggest that self-observation, self-monitoring, and self-reflection play a key role in developing problem solving strategies. We argue that studying these introspective processes will require researchers to systematically ask subjects to introspect. However, we document that cognitive science textbooks dismiss introspection and as a consequence introspective methods are not used in problem solving research, even when it would be appropriate. We conclude that research on problem solving would benefit from embracing introspection rather than dismissing it.</p>
1
https://docs.lib.purdue.edu/jps/vol6/iss1/4
oai:docs.lib.purdue.edu:jps-1137
2012-10-17T19:26:03Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Contents
Article
1
https://docs.lib.purdue.edu/jps/vol5/iss1/1
oai:docs.lib.purdue.edu:jps-1139
2012-10-17T19:28:57Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Editor's Introduction
van Rooij, Iris
Article
1
https://docs.lib.purdue.edu/jps/vol5/iss1/2
oai:docs.lib.purdue.edu:jps-1140
2012-10-17T19:30:31Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Indentations and Starting Points in Traveling Sales Tour Problems: Implications for Theory
MacGregor, James N
problem solving
optimization
convexity
perception of shorter paths
Article
<p>A complete, non-trivial, traveling sales tour problem contains at least one “indentation”, where nodes in the interior of the point set are connected between two adjacent nodes on the boundary. Early research reported that human tours exhibited fewer such indentations than expected. A subsequent explanation proposed that this was because the observed human tours were close to the optimal, and the optimal tours happened to have few indentations. The present article reports two experiments. The first was designed to test the “few indentations” hypothesis under more stringent conditions than previously, by including point sets with two (near) optimal solutions that had a different number of indentations. For these critical point sets, participants produced the optimal solution with fewer indentations significantly more often than the alternative optimal solution. In addition, participants’ solutions started on boundary points significantly more often than by chance. A second experiment tested whether the preference for fewer indentations is the result of a conscious strategy, or the product of the processes that generate a solution. The results supported the latter conclusion. The implications for theories of human tour generation are discussed.</p>
1
https://docs.lib.purdue.edu/jps/vol5/iss1/3
oai:docs.lib.purdue.edu:jps-1141
2012-10-17T19:32:40Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Relevancy in Problem Solving: A Computational Framework
Kwisthout, Johan
relevancy
abstraction
computational complexity
formal modeling
problem solving
Article
<p>When computer scientists discuss the computational complexity of, for example, finding the shortest path from building A to building B in some town or city, their starting point typically is a formal description of the problem at hand, e.g., a graph with weights on every edge where buildings correspond to vertices, routes between buildings to edges, and route-distances to edge-weights. Given such a formal description, either tractability or intractability of the problem is established, by proving that the problem either enjoys a polynomial time algorithm or is NP-hard. However, this problem description is in fact an abstraction of the actual problem of being in A and desiring to go to B: it focuses on the relevant aspects of the problem (e.g., distances between landmarks and crossings) and leaves out a lot of irrelevant details.</p>
<p>This abstraction step is often overlooked, but may well contribute to the overall complexity of solving the problem at hand. For example, it appears that “going from A to B” is rather easy to abstract: it is fairly clear that the distance between A and the next crossing is relevant, and that the color of the roof of B is typically not. However, when the problem to be solved is “make X love me”, where the current state is (assumed to be) “X doesn’t love me”, it is hard to agree on all the relevant aspects of this problem.</p>
<p>In this paper a computational framework is presented in order to formally investigate the notion of relevance in finding a suitable problem representation. It is shown that it is in itself intractable in general to find a minimal relevant subset of all problem dimensions that might or might not be relevant to the problem. Starting from a computational complexity stance, this paper aims to contribute a computational framework of ‘relevancy’ in problem solving, in order to be able to separate ‘easy to abstract’ from ‘hard to abstract’ problems. This framework is then used to discuss results in the literature on representation, (insight) problem solving and individual differences in the abstraction task, e.g., when experts in a particular domain are compared with novice problem solvers.</p>
1
https://docs.lib.purdue.edu/jps/vol5/iss1/4
oai:docs.lib.purdue.edu:jps-1144
2012-10-17T19:40:02Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
The Problems with Problem Solving: Reflections on the Rise, Current Status, and Possible Future of a Cognitive Research Paradigm
Ohlsson, Stellan
action retrieval
cognitive architecture
evaluation function
goal
heuristic search
methodology
problem perception
problem solving
problem space
search strategy
subgoal
think-aloud
Article
<p>The research paradigm invented by Allen Newell and Herbert A. Simon in the late 1950s dominated the study of problem solving for more than three decades. But in the early 1990s, problem solving ceased to drive research on complex cognition. As part of this decline, Newell and Simon’s most innovative research practices – especially their method for inducing subjects’ strategies from verbal protocols - were abandoned. In this essay, I summarize Newell and Simon’s theoretical and methodological innovations and explain why their strategy identification method did not become a standard research tool. I argue that the method lacked a systematic way to aggregate data, and that Newell and Simon’s search for general problem solving strategies failed. Paradoxically, the theoretical vision that led them to search elsewhere for general principles led researchers away from studies of complex problem solving. Newell and Simon’s main enduring contribution is the theory that people solve problems via heuristic search through a problem space. This theory remains the centerpiece of our understanding of how people solve unfamiliar problems, but it is seriously incomplete. In the early 1970s, Newell and Simon suggested that the field should focus on the question where problem spaces and search strategies come from. I propose a breakdown of this overarching question into five specific research questions. Principled answers to those questions would expand the theory of heuristic search into a more complete theory of human problem solving.</p>
1
https://docs.lib.purdue.edu/jps/vol5/iss1/7
oai:docs.lib.purdue.edu:jps-1142
2012-10-17T19:35:39Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Human Performance on Hard Non-Euclidean Graph Problems: Vertex Cover
Carruthers, Sarah
Masson, Michael E. J.
Stege, Ulrike
computational complexity
vertex cover
human performance
Article
<p>Recent studies on a computationally hard visual optimization problem, the Traveling Salesperson Problem (TSP), indicate that humans are capable of finding close to optimal solutions in near-linear time. The current study is a preliminary step in investigating human performance on another hard problem, the Minimum Vertex Cover Problem, in which solvers attempt to find a smallest set of vertices that ensures that every edge in an undirected graph is incident with at least one of the selected vertices. We identify appropriate measures of performance, examine features of problem instances that impact performance, and describe strategies typically employed by participants to solve instances of the Vertex Cover problem.</p>
1
https://docs.lib.purdue.edu/jps/vol5/iss1/5
oai:docs.lib.purdue.edu:jps-1143
2012-10-17T19:37:56Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Insight Problem Solving: A Critical Examination of the Possibility of Formal Theory
Batchelder, William H.
Alexander, Gregory E.
Insight problems
move problems
modularity
problem representation
Article
<p>This paper provides a critical examination of the current state and future possibility of formal cognitive theory for insight problem solving and its associated “aha!” experience. Insight problems are contrasted with move problems, which have been formally defined and studied extensively by cognitive psychologists since the pioneering work of Alan Newell and Herbert Simon. To facilitate our discussion, a number of classical brainteasers are presented along with their solutions and some conclusions derived from observing the behavior of many students trying to solve them. Some of these problems are interesting in their own right, and many of them have not been discussed before in the psychological literature. The main purpose of presenting the brainteasers is to assist in discussing the status of formal cognitive theory for insight problem solving, which is argued to be considerably weaker than that found in other areas of higher cognition such as human memory, decision-making, categorization, and perception. We discuss theoretical barriers that have plagued the development of successful formal theory for insight problem solving. A few suggestions are made that might serve to advance the field.</p>
1
https://docs.lib.purdue.edu/jps/vol5/iss1/6
oai:docs.lib.purdue.edu:jps-1149
2013-04-18T19:38:17Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Front Matter
Article
1
https://docs.lib.purdue.edu/jps/vol5/iss2/1
oai:docs.lib.purdue.edu:jps-1150
2013-04-18T19:54:40Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
A Comparison of Reinforcement Learning Models for the Iowa Gambling Task Using Parameter Space Partitioning
Steingroever, Helen
Wetzels, Ruud
Wagenmakers, Eric-Jan
decision making
loss aversion
Expectancy Valence model
Prospect Valence Learning model
Article
<p>The Iowa gambling task (IGT) is one of the most popular tasks used to study decisionmaking deficits in clinical populations. In order to decompose performance on the IGT in its constituent psychological processes, several cognitive models have been proposed (e.g., the Expectancy Valence (EV) and Prospect Valence Learning (PVL) models). Here we present a comparison of three models—the EV and PVL models, and a combination of these models (EV-PU)—based on the method of parameter space partitioning. This method allows us to assess the choice patterns predicted by the models across their entire parameter space. Our results show that the EV model is unable to account for a frequency-of-losses effect, whereas the PVL and EV-PU models are unable to account for a pronounced preference for the bad decks with many switches. All three models underrepresent pronounced choice patterns that are frequently seen in experiments. Overall, our results suggest that the search of an appropriate IGT model has not yet come to an end.</p>
1
https://docs.lib.purdue.edu/jps/vol5/iss2/2
oai:docs.lib.purdue.edu:jps-1151
2013-04-18T19:54:07Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Effects of Cluster Location on Human Performance on the Traveling Salesperson Problem
MacGregor, James N
problem solving
optimization
clustering
Article
<p>Most models of human performance on the traveling salesperson problem involve clustering of nodes, but few empirical studies have examined effects of clustering in the stimulus array. A recent exception varied degree of clustering and concluded that the more clustered a stimulus array, the easier a TSP is to solve (Dry, Preiss, & Wagemans, 2012). However, a limitation to this conclusion arises because degree of clustering may have been partially confounded with cluster location. An experiment was conducted to test the effects of cluster location while holding degree of clustering constant. Stimuli with a cluster near a boundary were solved more quickly and accurately than stimuli with the same cluster located more centrally. The results support and extend the previous findings of MacGregor, Ormerod, & Chronicle (1999). They also qualify the results of Dry et al. (2012). To the extent that degree of clustering may have been confounded with the location of clusters in their stimuli, it is unclear to what extent each factor may have affected performance.</p>
1
https://docs.lib.purdue.edu/jps/vol5/iss2/3
oai:docs.lib.purdue.edu:jps-1153
2013-04-18T20:01:33Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Perspectives on Problem Solving in Educational Assessment: Analytical, Interactive, and Collaborative Problem Solving
Greiff, Samuel
Holt, Daniel V.
Funke, Joachim
problem solving
large-scale assessment
PISA
analytical problem solving
interactive problem solving
collaborative problem solving
complex problem solving
Article
<p>Problem solving has received broad public interest as an important competency in modern societies. In educational large-scale assessments paper-pencil based analytical problem solving was included first (e.g., Programme for International Student Assessment, PISA 2003). With growing interest in more complex situations, the focus has shifted to interactive problem solving (e.g., PISA 2012) requiring identification and control of complex systems. In the future, collaborative problem solving represents the next step in assessing problem solving ability (e.g., PISA 2015). This paper describes these different approaches to assessing problem solving ability in large-scale assessments considering theoretical questions as well as assessment issues. For each of the three types of problem solving, the definition and understanding of the construct is explained, items examples are shown together with some empirical results, and limitations of the respective approach are discussed. A final discussion centers on the connection of cognitive and differential psychology within educational research and assessment.</p>
1
https://docs.lib.purdue.edu/jps/vol5/iss2/5
oai:docs.lib.purdue.edu:jps-1152
2013-04-18T19:57:48Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
On Evaluating Human Problem Solving of Computationally Hard Problems
Carruthers, Sarah
Stege, Ulrike
problem solving
computational complexity
intractability
algorithmic level theories
cognitive functions
Article
<p>This article is concerned with how computer science, and more exactly computational complexity theory, can inform cognitive science. In particular, we suggest factors to be taken into account when investigating how people deal with computational hardness. This discussion will address the two upper levels of Marr’s Level Theory: the computational level and the algorithmic level. Our reasons for believing that humans indeed deal with hard cognitive functions are threefold: (1) Several computationally hard functions are suggested in the literature, e.g., in the areas of visual search, visual perception and analogical reasoning, linguistic processing, and decision making. (2) People appear to be attracted to computationally hard recreational puzzles and games. Examples of hard puzzles include Sudoku, Minesweeper, and the 15-Puzzle. (3) A number of research articles in the area of human problem solving suggest that humans are capable of solving hard computational problems, like the Euclidean Traveling Salesperson Problem, quickly and near-optimally.</p>
<p>This article gives a brief introduction to some theories and foundations of complexity theory and motivates the use of computationally hard problems in human problem solving with a short survey of known results of human performance, a review of some computationally hard games and puzzles, and the connection between complexity theory and models of cognitive functions. We aim to illuminate the role that computer science, in particular complexity theory, can play in the study of human problem solving. Theoretical computer science can provide a wealth of interesting problems for human study, but it can also help to provide deep insight into these problems. In particular, we discuss the role that computer science can play when choosing computational problems for study and designing experiments to investigate human performance. Finally, we enumerate issues and pitfalls that can arise when choosing computationally hard problems as the subject of study, in turn motivating some interesting potential future lines of study. The pitfalls addressed include: choice of presentation and representation of problem instances, evaluation of problem comprehension, and the role of cognitive support in experiments. Our goal is not to exhaustively list all the ways in which these choices may impact experimental studies, but rather to provide a few simple examples in order to highlight possible pitfalls.</p>
1
https://docs.lib.purdue.edu/jps/vol5/iss2/4
oai:docs.lib.purdue.edu:jps-1154
2015-02-13T17:15:45Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Conceptual Transformation and Cognitive Processes in Origami Paper Folding
Tenbrink, Thora
Taylor, Holly A.
problem solving
instructions
text interpretation
cognitive processes
verbal data analysis
reconceptualization
Article
<p>Research on problem solving typically does not address tasks that involve following detailed and/or illustrated step-by-step instructions. Such tasks are not seen as cognitively challenging problems to be solved. In this paper, we challenge this assumption by analyzing verbal protocols collected during an Origami folding task. Participants verbalised thoughts well beyond reading or reformulating task instructions, or commenting on actions. In particular, they compared the task status to pictures in the instruction, evaluated the progress so far, referred to previous experience, expressed problems and confusions, and—crucially—added complex thoughts and ideas about the current instructional step. The last two categories highlight the fact that participants conceptualised this spatial task as a problem to be solved, and used creativity to achieve this aim. Procedurally, the verbalisations reflect a typical order of steps:<em> reading—reformulating—reconceptualising—evaluating.</em> During reconceptualisation, the creative range of spatial concepts represented in language highlights the complex mental operations involved when transferring the two-dimensional representation into the real world. We discuss the implications of our findings in terms of problem solving as a multilayered process involving diverse types of cognitive effort, consider parallels to known conceptual challenges involved in interpreting spatial descriptions, and reflect on the benefit of reconceptualisation for cognitive processes.</p>
1
https://docs.lib.purdue.edu/jps/vol8/iss1/1
oai:docs.lib.purdue.edu:jps-1155
2013-10-10T20:02:41Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Solving Large Problems with a Small Working Memory
Pizlo, Zygmunt
Stefanov, Emil
Article
<p>We describe an important elaboration of our multiscale/multiresolution model for solving the Traveling Salesman Problem (TSP). Our previous model emulated the non-uniform distribution of receptors on the human retina and the shifts of visual attention. This model produced near-optimal solutions of TSP in linear time by performing hierarchical clustering followed by a sequence of coarse-to-fine approximations of the tour. Linear time complexity was related to the minimal amount of search performed by the model, which posed minimal requirements on the size of the working memory. The new model implements the small working memory requirement. The model only stores information about as few as 2–5 clusters at any one time in the solution process. This requirement matches the known capacity of human working memory. We conclude by speculating that this model provides a possible explanation of how the human mind can effectively deal with very large search spaces.</p>
1
https://docs.lib.purdue.edu/jps/vol6/iss1/5
oai:docs.lib.purdue.edu:jps-1156
2013-10-10T19:26:27Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Human Problem Solving in 2012
Funke, Joachim
problem solving
bibliography
Article
<p>This paper presents a bibliography of 263 references related to human problem solving, arranged by subject matter. The references were taken from PsycInfo and Academic Premier database. Journal papers, book chapters, and dissertations are included. The topics include human development, education, neuroscience, and research in applied settings. It is argued that researchers are more and more engaged with problem solving research because of its centrality in human actions and because society needs advice from science in understanding and solving complex problems.</p>
1
https://docs.lib.purdue.edu/jps/vol6/iss1/3
oai:docs.lib.purdue.edu:jps-1157
2013-10-10T19:40:32Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Front Matter
Article
1
https://docs.lib.purdue.edu/jps/vol6/iss1/1
oai:docs.lib.purdue.edu:jps-1158
2013-10-10T16:59:46Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Editor's Introduction
Pizlo, Zygmunt
Article
1
https://docs.lib.purdue.edu/jps/vol6/iss1/2
oai:docs.lib.purdue.edu:jps-1159
2014-12-05T20:13:05Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
An Investigation of Starting Point Preferences in Human Performance on Traveling Salesman Problems
MacGregor, James N
Traveling salesman problem
starting point
optimization
perceptual salience
problem solving
Article
<p>Previous studies have shown that people start traveling sales problem tours significantly more often from boundary than from interior nodes. There are a number of possible reasons for such a tendency: first, it may arise as a direct result of the processes involved in tour construction; second, boundary points may be perceptually more salient than interior points, and selected for that reason; third, starting from the boundary may make the task easier or be more likely to result in a better tour than starting from the interior. The present research investigated each of these possibilities by analyzing start point frequencies in previously unpublished data and by conducting an experiment. The analysis of start points provided some slight but contradictory support for the hypothesis that start selections result from the process of tour construction, but no evidence for the perceptual salience explanation. The experiment required participants to start tours either from a boundary or from an interior point, to test whether there was an effect on the quality of tour construction. No evidence was found that starting point affected either the length of tours or the time required to produce them. However, there was some indication that starting from a central location may be more likely to result in crossed arcs.</p>
1
https://docs.lib.purdue.edu/jps/vol7/iss1/10
oai:docs.lib.purdue.edu:jps-1160
2014-12-05T20:12:04Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Fast and Efficient Discrimination of Traveling Salesperson Problem Stimulus Difficulty.
Dry, Matthew J
Fontaine, Elizabeth L
Article
<p>The Travelling Salesperson Problem (TSP) is a computationally difficult combinatorial optimization problem. In spite of its relative difficulty human solvers are able to generate close-to-optimal solutions in a close-to-linear time frame, and it has been suggested that this is due to the visual system’s inherent sensitivity to certain geometric properties of TSP stimuli. In the current study we employed a novel experimental paradigm in which we presented participants with sets of four TSP stimuli that varied in terms of their relative solution difficulty and asked them to indicate which of the four stimuli they would prefer to solve. The results indicated that the participants’ choice frequencies followed the same ordering as the stimuli’s empirical solution difficulty; i.e., easy-to-solve stimuli were chosen with a higher frequency than hard-to-solve stimuli. It is suggested that these results provide further evidence of the speed and efficiency of human processing of TSPs, and provide further evidence implicating the role of rapid visuo-perceptual organization in generating TSP solutions. An analysis of the geometric properties of the stimuli uncovered a number of factors that may have influenced the choice preferences of participants in the current experiment, and the performance quality of participants in previous experiments.</p>
1
https://docs.lib.purdue.edu/jps/vol7/iss1/9
oai:docs.lib.purdue.edu:jps-1161
2014-11-07T15:00:08Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Persistent and Pernicious Errors in Algebraic Problem Solving
Booth, Julie L.
Barbieri, Christina
Eyer, Francie
Pare-Blagoev, E. Juliana
error analysis
problem solving
algebra
Special Topic in Problem Solving
<p>Students hold many misconceptions as they transition from arithmetic to algebraic thinking, and these misconceptions can hinder their performance and learning in the subject. To identify the errors in Algebra I which are most persistent and pernicious in terms of predicting student difficulty on standardized test items, the present study assessed algebraic misconceptions using an in-depth error analysis on algebra students’ problem solving efforts at different points in the school year. Results indicate that different types of errors become more prominent with different content at different points in the year, and that there are certain types of errors that, when made during different levels of content are indicative of math achievement difficulties. Recommendations for the necessity and timing of intervention on particular errors are discussed.</p>
1
https://docs.lib.purdue.edu/jps/vol7/iss1/3
oai:docs.lib.purdue.edu:jps-1162
2014-11-10T14:55:53Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Effects of Cover Stories on Problem Solving in a Statistics Course
Ricks, Travis Rex
Wiley, Jennifer
Problem Solving
Statistics
Expertise
Knowledge
Special Topic in Problem Solving
<p>Does having more knowledge or interest in the topics used in example problems facilitate or hinder learning in statistics? Undergraduates enrolled in Introductory Psychology received a lesson on central tendency. Following the lesson, half of the students completed a worksheet with a baseball cover story while the other half received a weather cover story. Learning was assessed using a quiz that contained two kinds of items: computation and explanation. Measures of baseball knowledge and interest in baseball were collected. The results indicated that overall the students performed better on computation items than explanation items. The weather example led to better performance on the explanation items than the baseball example. No differences were seen in performance on the quiz as a function of gender, prior knowledge, or interest. If anything, the results indicated that interest in baseball seemed to hinder learning in the baseball condition. Possible reasons for differences in performance due to the cover story are discussed.</p>
1
https://docs.lib.purdue.edu/jps/vol7/iss1/6
oai:docs.lib.purdue.edu:jps-1163
2014-11-07T16:10:55Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Rewarding Multitasking: Negative Effects of an Incentive on Problem Solving under Divided Attention
Wieth, Mareike B.
Burns, Bruce D.
Multitasking
Incentives
Problem Solving
Special Topic in Problem Solving
<p>Research has consistently shown negative effects of multitasking on tasks such as problem solving. This study was designed to investigate the impact of an incentive when solving problems in a multitasking situation. Incentives have generally been shown to increase problem solving (e.g., Wieth and Burns, 2006), however, it is unclear whether an incentive can increase problem solving while attentional resources are divided. Participants were either given an incentive or not and asked to complete incremental and insight problems while either in a dual-task or single task condition. After solving the problems participants were given a surprise memory test. Results showed that the incentive only led to increases in problem solving in the single task condition but not the dual-task condition. Furthermore, results showed that an incentive in the dual-task condition led to an increase in recall of irrelevant information. These findings indicate that an incentive cannot ameliorate the detrimental effects of multitasking when problem solving and may even lead to an increase in irrelevant information processing.</p>
1
https://docs.lib.purdue.edu/jps/vol7/iss1/7
oai:docs.lib.purdue.edu:jps-1164
2014-11-07T16:15:43Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Enclothed Cognition and Controlled Attention during Insight Problem-Solving
Van Stockum, Charles A., Jr.
DeCaro, Marci S.
working memory
attention
problem-solving
insight
enclothed cognition
individual differences
situational factors
Special Topic in Problem Solving
<p>Individual differences in working memory capacity (WMC) increase the ability, and tendency, to devote greater attentional control to a task—improving performance on a wide range of skills. In addition, recent research on enclothed cognition demonstrates that the situational influence of wearing a white lab coat increases controlled attention, due to the symbolic meaning and physical experience of wearing the coat. We examined whether these positive influences on attentional control lead to negative performance outcomes on insight problem-solving, a task thought to rely on associative processes that operate largely outside of explicit attentional control. Participants completed matchstick arithmetic problems while either wearing a white lab coat or in a no-coat control condition. Higher WMC was associated with lower insight problem-solving accuracy in the no-coat condition. In the coat condition, the insight problem-solving accuracy of lower WMC individuals dropped to the level of those higher in WMC. These results indicate that wearing a white lab coat led individuals to increase attentional control towards problem solving, hindering even lower WMC individuals from engaging in more diffuse, associative problem-solving processes, at which they otherwise excel. Trait and state factors known to increase controlled attention and improve performance on more attention-demanding tasks interact to hinder insight problem-solving.</p>
1
https://docs.lib.purdue.edu/jps/vol7/iss1/8
oai:docs.lib.purdue.edu:jps-1165
2014-11-07T18:51:07Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Activation of Operational Thinking During Arithmetic Practice Hinders Learning And Transfer
Chesney, Dana L
McNeil, Nicole M
mathematics learning
arithmetic practice
conceptual understanding
early algebra
symbolic understanding
Special Topic in Problem Solving
<p>Many children in the U.S. initially come to understand the equal sign operationally, as a symbol meaning “add up the numbers” rather than relationally, as an indication that the two sides of an equation share a common value. According to a change-resistance account (McNeil & Alibali, 2005), children's operational ways of thinking are never erased, and when activated, can interfere with mathematics learning and performance, even in educated adults. To test this theory, undergraduates practiced unfamiliar multiplication facts (e.g., 17-times table) in one of three conditions that differed in terms of how the equal sign was represented in the problems. In the operational words condition, the equal sign was replaced by operational words (e.g., "multiplies to"). In the relational words condition, the equal sign was replaced by relational words (e.g., "is equivalent to"). In the control condition, the equal sign was used in all problems. The hypothesis was that undergraduates' fluency with practiced facts and transfer problems would be hindered in the operational words condition compared to the other conditions. Results supported this hypothesis, indicating that the activation of operational thinking is indeed detrimental to learning and transfer, even in educated adults.</p>
1
https://docs.lib.purdue.edu/jps/vol7/iss1/4
oai:docs.lib.purdue.edu:jps-1166
2014-11-07T15:37:46Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Wait for it . . . Delaying Instruction Improves Mathematics Problem Solving: A Classroom Study
Loehr, Abbey Marie
Fyfe, Emily R
Rittle-Johnson, Bethany
mathematics learning
problem solving
exploratory learning
direct instruction
Special Topic in Problem Solving
<p>Engaging learners in exploratory problem-solving activities prior to receiving instruction (i.e., explore-instruct approach) has been endorsed as an effective learning approach. However, it remains unclear whether this approach is feasible for elementary-school children in a classroom context. In two experiments, second-graders solved mathematical equivalence problems either before or after receiving brief conceptual instruction. In Experiment 1 (n = 41), the explore-instruct approach was less effective at supporting learning than an instruct-solve approach. However, it did not include a common, but often overlooked feature of an explore-instruct approach, which is provision of a knowledge-application activity after instruction. In Experiment 2 (n = 47), we included a knowledge-application activity by having all children check their answers on previously solved problems. The explore-instruct approach led to superior learning than an instruct-solve approach. Findings suggest promise for an explore-instruct approach, provided learners have the opportunity to apply knowledge from instruction.</p>
1
https://docs.lib.purdue.edu/jps/vol7/iss1/5
oai:docs.lib.purdue.edu:jps-1167
2014-11-07T14:59:13Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
What Are the Odds? A Practical Guide to Computing and Reporting Bayes Factors
Jarosz, Andrew F.
Wiley, Jennifer
Statistics
Bayes Factor
Special Topic in Problem Solving
<p>The purpose of this paper is to provide an easy template for the inclusion of the Bayes factor in reporting experimental results, particularly as a recommendation for articles in the <em>Journal of Problem Solving</em>. The Bayes factor provides information with a similar purpose to the <em>p</em>-value – to allow the researcher to make statistical inferences from data provided by experiments. While the <em>p</em>-value is widely used, the Bayes factor provides several advantages, particularly in that it allows the researcher to make a statement about the alternative hypothesis, rather than just the null hypothesis. In addition, it provides a clearer estimate of the amount of evidence present in the data. Building on previous work by authors such as Wagenmakers (2007), Rouder et al. (2009), and Masson (2011), this article provides a short introduction to Bayes factors, before providing a practical guide to their computation using examples from published work on problem solving.</p>
1
https://docs.lib.purdue.edu/jps/vol7/iss1/2
oai:docs.lib.purdue.edu:jps-1169
2015-12-21T21:58:20Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Development of the PEBL Traveling Salesman Problem Computerized Testbed
Mueller, Shane T
Perelman, Brandon S
Tan, Yin Yin
Thanasuan, Kejkaew
Traveling Salesman Problem
individual differences
cognitive testing
problem solving
Article
<p>The traveling salesman problem (TSP) is a combinatorial optimization problem that requires finding the shortest path through a set of points (“cities”) that returns to the starting point. Because humans provide heuristic near-optimal solutions to Euclidean versions of the problem, it has sometimes been used to investigate human visual problem solving ability. The TSP is also similar to a number of tasks commonly used for neuropsychological assessment (such as the trail-making test), and so its utility in assessing reliable individual differences in problem solving has sometimes been examined. Nevertheless, the task has seen little widespread use in clinical and assessment domains, in part because no standard software implementation or item set is widely available with known psychometric properties. In this paper, we describe a computerized version of TSP running in the free and open source Psychology Experiment Building Language (PEBL). The PEBL TSP task is designed to be suitable for use within a larger battery of tests, and to examine both standard and custom TSP node configurations (i.e., problems). We report the results of a series of experiments that help establish the test’s reliability and validity. The first experiment examines test-retest reliability, establishes that the quality of solutions in the TSP are not impacted by mild physiological strain, and demonstrates how solution quality obtained by individuals in a physical version is highly correlated with solution quality obtained in the PEBL version. The second experiment evaluates a larger set of problems, and uses the data to identify a small subset of tests that have maximal coherence. A third experiment examines test-retest reliability of this smaller set that can be administered in about five minutes, and establishes that these problems produce composite scores with moderately high (R = .75) test-retest reliability, making it suitable for use in many assessment situations, including evaluations of individual differences, personality, and intelligence testing.</p>
1
https://docs.lib.purdue.edu/jps/vol8/iss1/4
oai:docs.lib.purdue.edu:jps-1171
2014-11-07T14:39:06Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Editor's Introduction
Wiley, Jennifer
Front Matter
1
https://docs.lib.purdue.edu/jps/vol7/iss1/1
oai:docs.lib.purdue.edu:jps-1172
2015-04-03T19:07:42Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Differential Modulation of Performance in Insight and Divergent Thinking Tasks with tDCS
Goel, Vinod
Eimontaite, Iveta
Goel, Amit
Schindler, Igor
enhancing creativity
tDCS
insight
fluency
semantic spread
mental set shift
temporal lobes
Article
<p>While both insight and divergent thinking tasks are used to study creativity, there are reasons to believe that the two may call upon very different mechanisms. To explore this hypothesis, we administered a verbal insight task (riddles) and a divergent thinking task (verbal fluency) to 16 native English speakers and 16 non-native English speakers after they underwent Transcranial Direct Current Stimulation (tDCS) of the left middle temporal gyrus and right temporo- parietal junction. We found that, in the case of the insight task the depolarization of right temporo-parietal junction and hyperpolarization of left middle temporal gyrus resulted in increased performance, relative to both the control condition and the reverse stimulation condition in both groups (non-native > native speakers). However, in the case of the divergent thinking task, the same pattern of stimulation resulted in a decrease in performance, compared to the reverse stimulation condition, in the non-native speakers. We explain this dissociation in terms of differing task demands of divergent thinking and insight tasks and speculate that the greater sensitivity of non-native speakers to tDCS stimulation may be a function of less entrenched neural networks for non-native languages.</p>
1
https://docs.lib.purdue.edu/jps/vol8/iss1/2
oai:docs.lib.purdue.edu:jps-1173
2015-07-22T11:18:11Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Human-Machine Cooperation in Large-Scale Multimedia Retrieval: A Survey
Shirahama, Kimiaki
Grzegorzek, Marcin
Indurkhya, Bipin
large-scale multimedia retrieval
humanmachine cooperation
machine-based methods
human-based methods
Article
<p><em>Large-Scale Multimedia Retrieval</em>(LSMR) is the task to fast analyze a large amount of multimedia data like images or videos and accurately find the ones relevant to a certain semantic meaning. Although LSMR has been investigated for more than two decades in the fields of multimedia processing and computer vision, a more interdisciplinary approach is necessary to develop an LSMR system that is really meaningful for humans. To this end, this paper aims to stimulate attention to the LSMR problem from diverse research fields. By explaining basic terminologies in LSMR, we first survey several representative methods in chronological order. This reveals that due to prioritizing the generality and scalability for large-scale data, recent methods interpret semantic meanings with a completely different mechanism from humans, though such humanlike mechanisms were used in classical heuristic-based methods. Based on this, we discuss <em>human-machine cooperation,</em> which incorporates knowledge about human interpretation into LSMR without sacrificing the generality and scalability. In particular, we present three approaches to human-machine cooperation (<em>cognitive, ontological,</em> and <em>adaptive</em>), which are attributed to cognitive science, ontology engineering, and metacognition, respectively. We hope that this paper will create a bridge to enable researchers in different fields to communicate about the LSMR problem and lead to a ground-breaking next generation of LSMR systems.</p>
1
https://docs.lib.purdue.edu/jps/vol8/iss1/3
oai:docs.lib.purdue.edu:jps-1180
2016-01-29T19:51:53Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Does Comparing Informal and Formal Procedures Promote Mathematics Learning? The Benefits of Bridging Depend on Attitudes Toward Mathematics
Hattikudur, Shanta
Sidney, Pooja G.
Alibali, Martha W
mathematics
comparison
instruction
conceptual knowledge
math attitudes
algebra
Article
<p>Students benefit from learning multiple procedures for solving the same or related problems. However, past research on comparison instruction has focused on comparing multiple formal procedures. This study investigated whether the benefits of comparing procedures extend to comparisons that involve informal and formal procedures. We also examined how learner characteristics, including prior knowledge and attitudes toward mathematics, affect learning from comparing procedures. We addressed these issues in college students' learning procedures for solving systems of equations problems in algebra. Learners who liked mathematics learned equally well whether they received comparison or sequential instruction. However, among learners who did not like mathematics, instruction that included support for comparisons between the formal and informal procedures led to greater gains in conceptual knowledge than did sequential instruction of the procedures.</p>
1
https://docs.lib.purdue.edu/jps/vol9/iss1/2
oai:docs.lib.purdue.edu:jps-1181
2016-01-29T19:45:38Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Alternative Representations in Algebraic Problem Solving: When are Graphs Better Than Equations?
Mielicki, Marta K
Wiley, Jennifer
Multiple representations
algebra
slope
Article
<p>Successful algebraic problem solving entails adaptability of solution methods using different representations. Prior research has suggested that students are more likely to prefer symbolic solution methods (equations) over graphical ones, even when graphical methods should be more efficient. However, this research has not tested how representation format might affect solution success, and whether the efficiency of solution varies depending on the nature of the problem solving task. This study addressed the question of whether symbolic or graphical representation format provides different affordances with respect to two different types of problems: computation and interpretation. Graphical representation was found to facilitate problem solving among college students, and problems that required the comparison of slopes were more difficult when presented in a symbolic format than in graphical format.</p>
1
https://docs.lib.purdue.edu/jps/vol9/iss1/1
oai:docs.lib.purdue.edu:jps-1182
2016-03-23T16:36:14Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Problem Solving as an Encoding Task: A Special Case of the Generation Effect
Kizilirmak, Jasmin M
Wiegmann, Berit
Richardson-Klavehn, Alan
insight
problem-solving
generation effect
long-term memory
learning
Article
<p>Recent evidence suggests that solving problems through insight can enhance long-term memory for the problem and its solution. Previous findings have shown that generation of the solution as well as experiencing a feeling of Aha! can have a beneficial relationship to later memory. These findings lead to the question of how learning in problem-solving tasks in which a novel solution needs to be generated—such as in tasks used to study insight—differs from the classical generation effect. Because previous studies on learning from insight on one hand and the generation effect on the other hand have measured different types of memory, the present study examined two kinds of memory measures: indirect (solving old and new problems at test) and direct (recognition memory). At encoding, we manipulated whether participants had the chance to solve Compound Remote Associates Task items and compared later memory for generated solutions (generate condition) to solutions that were presented after failing to generate one (fail-to-generate condition), and to solutions that were presented without a chance at generation (read condition). Participants also reported if they had an Aha! experience for each problem. While both Aha! experiences and generated solutions were associated with more positive emotional responses, only the generation variable was associated with differences in later memory performance. While attempts to generate had an advantage over the read condition in recognition memory performance (generate > fail-to-generate > read), only when generation was successful did it enhance the solution rate of old items during testing (generate > read > fail-to-generate). Contrary to generation effects with other verbal stimuli, these results suggest that the generation effect in problem-solving tasks in which a novel solution needs to be found differs from the classical generation effect. Seeing a correct solution for a longer time (read) seems in the current case to be more helpful for solving the same problem later on, compared to being presented with the solution after a failed attempt at problem solving.</p>
1
https://docs.lib.purdue.edu/jps/vol9/iss1/5
oai:docs.lib.purdue.edu:jps-1183
2016-04-04T14:53:23Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Solving Classical Insight Problems Without Aha! Experience: 9 Dot, 8 Coin, and Matchstick Arithmetic Problems
Danek, Amory H.
Wiley, Jennifer
Öllinger, Michael
insight
problem solving
constraints
Aha! experience
9 dot
8 coin
matchstick
Article
<p>Insightful problem solving is a vital part of human thinking, yet very difficult to grasp. Traditionally, insight has been investigated by using a set of established “insight tasks,” assuming that insight has taken place if these problems are solved. Instead of assuming that insight takes place during every solution of the 9 Dot, 8 Coin, and Matchstick Arithmetic Problems, this study explored the likelihood that solutions evoked the “Aha! experience,” which is often regarded as the defining characteristic of insight. It was predicted that the rates of self-reported Aha! experiences might vary based on the necessary degree of constraint relaxation. The main assumption was that the likelihood of experiencing an Aha! would decrease with increasing numbers of constraints that must be relaxed, because several steps are needed to achieve a representational change and solve the problem, and thus, the main feature of suddenness of a solution might be lacking. The results supported this prediction, and demonstrated that in many cases participants do solve these classical insight problems without any Aha! experience. These results show the importance of obtaining insight ratings from participants to determine whether any given problem is solved with insight or not.</p>
1
https://docs.lib.purdue.edu/jps/vol9/iss1/4
oai:docs.lib.purdue.edu:jps-1184
2016-02-26T20:27:34Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Situative Creativity: Larger Physical Spaces Facilitate Thinking of Novel Uses for Everyday Objects
Chan, Joel
Nokes-Malach, Timothy J
Situative cognition
creative problem solving
metaphor
Article
<p>People often use spatial metaphors (e.g., think “laterally,” “outside the box”) to describe exploration of the problem space during creative problem solving. In this paper, we probe the potential cognitive underpinnings of these spatial metaphors. Drawing on theories of situative cognition, semantic foraging theory, and environmental psychology, we formulate and test the hypothesis that larger physical spaces can facilitate divergent (but not convergent) processes in problem space exploration. Across two experiments, participants worked on a battery of problem solving tasks intended to represent divergent (alternative uses, shape invention) and convergent (remote associates, letter extrapolation) problem solving processes in either a large or a small room. In Experiment 1, participants in the larger room produced more novel alternative uses for everyday objects, and created more novel shape inventions, but generated less practical alternative uses, than participants in the smaller room. In Experiment 2, participants in the larger room (including a variant larger room) also produced more novel alternative uses for everyday objects, and less practical alternative uses, than participants in a small room, but did not create more novel shape inventions. These results suggest that spatial metaphors for problem space exploration may reflect meaningful cognitive phenomena: People may be able to search more broadly in a problem space if they are in an environment where broad physical search is a salient affordance; however, this effect appears to be relatively small and may depend on having sufficiently motivated participants.</p>
1
https://docs.lib.purdue.edu/jps/vol9/iss1/3
oai:docs.lib.purdue.edu:jps-1186
2016-04-04T13:14:24Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Editor's Introduction
Wiley, Jennifer
problem solving
Editor's Introduction
<p>As noted in the last bibliography of Human Problem Solving compiled by Joachim Funke and reported in the <em>Journal of Problem Solving </em>in 2013, problem solving as a concept and as a research issue has been gaining more interest than ever before. Now in 2016, we can see that publications on the topic further increased to around 1,800 per year in both 2013 and 2014. The papers in this special issue come from two areas of problem solving research, mathematical and creative problem solving, which represent a good part of this growth trend. With this special issue, the journal has closed its first decade. We look forward to another decade of growth in research on important questions about the mental mechanisms underlying this cognitive ability.</p>
1
https://docs.lib.purdue.edu/jps/vol9/iss1/6
oai:docs.lib.purdue.edu:jps-1193
2018-01-08T19:48:52Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Heuristics for Comparing the Lengths of Completed E-TSP Tours: Crossings and Areas
MacGregor, James N
problem solving
heuristics
optimization
area judgments
Special Issue: Internal Representations in Human Problem Solving-Part 1
<p>The article reports three experiments designed to explore heuristics used in comparing the lengths of completed Euclidean Traveling Salesman Problem (E-TSP) tours. The experiments used paired comparisons in which participants judged which of two completed tours of the same point set was shorter. The first experiment manipulated two factors, the presence/absence of crossed arcs, and the relative areas of the enclosed polygons. Both factors significantly influenced judgments, with the absence of crossings and smaller areas being associated with shorter tours. The second experiment examined the effects of crossings only, and compared stimulus pairs using all possible combinations of no, one, and more than one crossing. The results showed a significant tendency for tours with one or more crossings to be judged longer than tours with none, while tours with more crossings were not judged to be longer than tours with only one. Apparently the mere presence of a crossing is sufficient to cause a tour to be judged as longer. The third experiment examined the effects of area only, and consisted of two parts. In the first part, participants judged which of two tours that differed in area was shorter. The results supported those of the first experiment, by finding that tours with smaller areas tended to be judged as shorter. In the second part of the experiment, participants judged the relative areas of each pair, to determine whether people can reliably differentiate the areas of such complex polygons. The results confirmed that they can, thereby supporting the feasibility of using differences in area as a heuristic to judge relative lengths. The results were discussed in terms of Carruthers’s (2015) proposal of goal modification and the suggestion is made that applying heuristics of the type identified may represent a specific form of goal modification.</p>
1
https://docs.lib.purdue.edu/jps/vol10/iss1/2
oai:docs.lib.purdue.edu:jps-1194
2017-07-27T14:25:58Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Algorithmic Puzzles: History, Taxonomies, and Applications in Human Problem Solving
Levitin, Anany
algorithmic puzzles
problem solving
insight
Article
<p>The paper concerns an important but underappreciated genre of algorithmic puzzles, explaining what these puzzles are, reviewing milestones in their long history, and giving two different ways to classify them. Also covered are major applications of algorithmic puzzles in cognitive science research, with an emphasis on insight problem solving, and the advantages of algorithmic puzzles over some other classes of problems used in insight research. The author proposes adding algorithmic puzzles as a separate category of insight problems, suggests 12 specific puzzles that could be useful for research in insight problem solving, and outlines several experiments dealing with other cognitive aspects of solving algorithmic puzzles.</p>
1
https://docs.lib.purdue.edu/jps/vol10/iss1/1
oai:docs.lib.purdue.edu:jps-1197
2019-02-07T20:53:09Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Deep Analogical Inference as the Origin of Hypotheses
Blokpoel, Mark
Wareham, Todd
Haselager, Pim
Toni, Ivan
van Rooij, Iris
abductive inference
hypothesis generation
analogy
computational-level model
Special Issue: Internal Representations in Human Problem Solving-Part 2
<p>The ability to generate novel hypotheses is an important problem-solving capacity of humans. This ability is vital for making sense of the complex and unfamiliar world we live in. Often, this capacity is characterized as an inference to the best explanation—selecting the “best” explanation from a given set of candidate hypotheses. However, it remains unclear where these candidate hypotheses originate from. In this paper we contribute to computationally explaining these origins by providing the contours of the computational problem solved when humans generate hypotheses. The origin of hypotheses, otherwise known as abduction proper, is hallmarked by seven properties: (1) isotropy, (2) open-endedness, (3) novelty, (4) groundedness, (5) sensibility, (6) psychological realism, and (7) computational tractability. In this paper we provide a computational-level theory of abduction proper that unifies the first six of these properties and lays the groundwork for the seventh property of computational tractability. We conjecture that abduction proper is best seen as a process of deep analogical inference.</p>
1
https://docs.lib.purdue.edu/jps/vol11/iss1/3
oai:docs.lib.purdue.edu:jps-1200
2018-01-25T19:09:32Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
The Role of the Goal in Solving Hard Computational Problems: Do People Really Optimize?
Carruthers, Sarah
Stege, Ulrike
Masson, Michael E. J.
problem solving
computational complexity
intractability
Special Issue: Internal Representations in Human Problem Solving-Part 2
<p>The role that the mental, or internal, representation plays when people are solving hard computational problems has largely been overlooked to date, despite the reality that this internal representation drives problem solving. In this work we investigate how performance on versions of two hard computational problems differs based on what internal representations can be generated. Our findings suggest that problem solving performance depends not only on the objective difficulty of the problem, and of course the particular problem instance at hand, but also on how feasible it is to encode the goal of the given problem. A further implication of these findings is that previous human performance studies using NP-hard problems may have, surprisingly, underestimated human performance on instances of problems of this class. We suggest ways to meaningfully frame human performance results on instances of computationally hard problems in terms of these problems’ computational complexity, and present a novel framework for interpreting results on problems of this type. The framework takes into account the limitations of the human cognitive system, in particular as it applies to the generation of internal representations of problems of this class.</p>
1
https://docs.lib.purdue.edu/jps/vol11/iss1/1
oai:docs.lib.purdue.edu:jps-1201
2018-01-08T19:53:29Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
The Roles of Internal Representation and Processing in Problem Solving Involving Insight: A Computational Complexity Perspective
Wareham, Todd
problem solving
insight
restructuring
computational complexity
ideal observer models
Special Issue: Internal Representations in Human Problem Solving-Part 1
<p>In human problem solving, there is a wide variation between individuals in problem solution time and success rate, regardless of whether or not this problem solving involves insight. In this paper, we apply computational and parameterized analysis to a plausible formalization of extended representation change theory (eRCT), an integration of problem solving by problem space search and insight as problem restructuring which proposes that this variation may be explainable by individuals having different problem representations and search heuristic choices. Our analyses establish not only the intractability of eRCT in general, but also sets of restrictions under which eRCT-based problem solving can and cannot be done quickly. As such, our analyses both prove that several conjectures about what makes problem solving under eRCT possible in practice are incomplete, in the sense that not all factors in the model whose restriction is responsible for efficient solvability are part of the explanation, and provide several new explanations that are complete.</p>
1
https://docs.lib.purdue.edu/jps/vol10/iss1/3
oai:docs.lib.purdue.edu:jps-1211
2018-01-08T19:55:38Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
Guest Editors’ Introduction
Carruthers, Sarah
Stege, Ulrike
Editor's Introduction
1
https://docs.lib.purdue.edu/jps/vol10/iss1/4
oai:docs.lib.purdue.edu:jps-1212
2018-10-25T18:32:20Z
publication:jps
publication:librariespublishing
publication:libraries
publication:pupoaj
The Role of Problem Representation in Producing Near-Optimal TSP Tours
Fleischer, Pierson
Hélie, Sébastien
Pizlo, Zygmunt
TSP
shortest path
log-polar transformation
Article
<p>Gestalt psychologists pointed out about 100 years ago that a key to solving difficult insight problems is to change the mental representation of the problem, as is the case, for example, with solving the six matches problem in 2D vs. 3D space. In this study we ask a different question, namely what representation is used when subjects solve search, rather than insight problems. Some search problems, such as the traveling salesman problem (TSP), are defined in the Euclidean plane on the computer monitor or on a piece of paper, and it seems natural to assume that subjects who solve a Euclidean TSP do so using a Euclidean representation. It is natural to make this assumption because the TSP task is defined in that space. We provide evidence that, on the contrary, subjects may produce TSP tours in the complex-log representation of the TSP city map. The complex-log map is a reasonable assumption here, because there is evidence suggesting that the retinal image is represented in the primary visual cortex as a complex-log transformation of the retina. It follows that the subject’s brain may be “solving” the TSP using complex-log maps. We conclude by pointing out that solving a Euclidean problem in a complex-log representation may be acceptable, even desirable, if the subject is looking for near-optimal, rather than optimal solutions.</p>
1
https://docs.lib.purdue.edu/jps/vol11/iss1/2