Topics in Cognitive Science 7 (2):351-367 (2015)

Abstract
Decision making in noisy and changing environments requires a fine balance between exploiting knowledge about good courses of action and exploring the environment in order to improve upon this knowledge. We present an experiment on a restless bandit task in which participants made repeated choices between options for which the average rewards changed over time. Comparing a number of computational models of participants’ behavior in this task, we find evidence that a substantial number of them balanced exploration and exploitation by considering the probability that an option offers the maximum reward out of all the available options
Keywords Dynamic decision making  Volatility  Uncertainty  Exploration‐exploitation trade‐off  Restless multi‐armed bandit task
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DOI 10.1111/tops.12145
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From Conditioning to Category Learning: An Adaptive Network Model.Mark A. Gluck & Gordon H. Bower - 1988 - Journal of Experimental Psychology: General 117 (3):227-247.

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