Learning to maximize reward rate: a model based on semi-Markov decision processes

When animals have to make a number of decisions during a limited time interval, they face a fundamental problem: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will...

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Bibliographic Details

Published in:	Frontiers in Neuroscience
Main Authors:	Arash eKhodadadi, Pegah eFakhari, jerome eBusemeyer
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2014-05-01
Subjects:	reinforcement learning decision threshold Speed-accuracy trade-off semi-Markov decision process average reward rate maximization sequential sampling models
Online Access:	http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00101/full