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1 results

  • 21 - Computational Models of Animal and Human Associative Learning

  • from Part III - Computational Modeling of Basic Cognitive Functionalities
  • Edited by Ron Sun, Rensselaer Polytechnic Institute, New York
  • Book:
    The Cambridge Handbook of Computational Cognitive Sciences
    Published online:
    21 April 2023
    Print publication:
    11 May 2023, pp 703-738

  • Summary

    This chapter provides a selective review of the issues that have dominated computational models of associative learning in recent decades. Associative learning research concerns the simplest and most fundamental processes by which humans and other animals come to predict events in their environment based on past experience. It has far-reaching implications for understanding adaptive and maladaptive human behavior. With a focus on Pavlovian conditioning and adjacent subdisciplines, this chapter explores how the prediction error learning algorithm has shaped understanding of competitive learning, selective attention, stimulus representation, and learning about absent events. A number of alternative computational approaches will be introduced, along with some remaining challenges in the computational modeling of human and animal associative learning.