Publication Summary and Abstract
Ashvin Shah (2012), Psychological and Neuroscientific Connections with Reinforcement Learning , in Marco Wiering and Martijn van Otterlo, editors, Reinforcement Learning: State of the Art, Chapter 16, pages 507--537, Springer-Verlag, Berlin Heidelberg.
The field of Reinforcement Learning (RL) was inspired in large part by research in animal behavior and psychology. Early research showed that animals can, through trial and error, learn to execute behavior that would eventually lead to some (presumably satisfactory) outcome, and decades of subsequent research was (and is still) aimed at discovering the mechanisms of this learning process. This chapter describes behavioral and theoretical research in animal learning that is directly related to fundamental concepts used in RL. It then describes neuroscientific research that suggests that animals and many RL algorithms use very similar learning mechanisms. Along the way, I highlight ways that research in computer science contributes to and can be inspired by research in psychology and neuroscience.
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