Decision Making under Uncertainty: A Neural Model based on Partially Observable Markov Decision Processes
A fundamental problem faced by animals is learning to select actions based on noisy sensory information and incomplete knowledge of the world. It has been suggested that the brain engages in Bayesian inference during perception but how such probabilistic representations are used to select actions ha...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2010-11-01
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| Series: | Frontiers in Computational Neuroscience |
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| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fncom.2010.00146/full |