Nonhuman animals show evidence for three types of concept learning: perceptual or similarity-based in which objects/stimuli are categorized based on physical similarity; relational in which one object/stimulus is categorized relative to another (e.g., same/different); and associative in which arbitrary stimuli become interchangeable with one another by virtue of a common association with another stimulus, outcome, or response. In this article, we focus on various methods for establishing associative concepts in nonhuman animals and evaluate data documenting the development of associative classes of stimuli. We also examine the nature of the common within-class representation of samples that have been associated with the same reinforced comparison response (i.e., many-to-one matching) by describing manipulations for distinguishing possible representations. Associative concepts provide one foundation for human language such that spoken and written words and the objects they represent become members of a class of interchangeable stimuli. The mechanisms of associative concept learning and the behavioral flexibility it allows, however, are also evident in the adaptive behaviors of animals lacking language.
associative concepts, equivalence, within-class representation, many-to-one matching
Date of this Version
Zentall, Thomas R.; Wasserman, Edward A.; and Urcuioli, Peter J., "Associative Concept Learning in Animals" (2014). Department of Psychological Sciences Faculty Publications. Paper 67.
This article may not exactly replicate the final version published in the SEAB journal. It is not the copy of record. This is the pre-peer reviewed version of the following article: Zentall, T.R., Wasserman, E.A., & Urcuioli, P.J. (2014). Associative Concept Learning in Animals. Journal of the Experimental Analysis of Behavior, 101(1), 130-151. http://dx.doi.org/10.1002/jeab.55, which has been published in final form at http://dx.doi.org/10.1002/jeab.55. Authors are not required to remove preprints posted prior to acceptance of the submitted version.