Reinforcement Learning

Reinforcement Learning

Darryl Charles (University of Ulster, Ireland), Colin Fyfe (University of Paisley, UK), Daniel Livingstone (University of Paisley, UK) and Stephen McGlinchey (University of Paisley, UK)
Copyright: © 2008 |Pages: 25
DOI: 10.4018/978-1-59140-646-4.ch012
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Abstract

Just as there are many different types of supervised and unsupervised learning, so there are many different types of reinforcement learning. Reinforcement learning is appropriate for an AI or agent which is actively exploring its environment and also actively exploring what actions are best to take in different situations. Reinforcement learning is so-called because, when an AI performs a beneficial action, it receives some reward which reinforces its tendency to perform that beneficial action again. An excellent overview of reinforcement learning (on which this brief chapter is based) is by Sutton and Barto (1998).

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