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Animals and artificial systems alike are faced with the problem of making inferences about their environments and choosing appropriate responses based on incomplete, uncertain and noisy data.
Probabilistic models and algorithms are flourishing in both life sciences and information sciences as ways of understanding the behavior of subjects and the neural processing underlying this behavior, and building robots and artificial agents that can function effectively in such circumstances.
The objective of this winter school is to present the latest advances in this subject, specifically addressing the following topics:
This winter school is a prolongation of the Bayesian Cognition workshop held in Paris in January 2006.