Bayesian approaches to modelling action selection

Abstract

We live in an uncertain world, and each decision may have many possible outcomes; choosing the best decision is thus complicated. This chapter describes recent research in Bayesian decision theory, which formalises the problem of decision making in the presence of uncertainty and often provides compact models that predict observed behaviour. With its elegant formalisation of the problems faced by the nervous system, it promises to become a major inspiration for studies in neuroscience.

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Cite this paper

@inproceedings{Berniker2011BayesianAT, title={Bayesian approaches to modelling action selection}, author={Max Berniker and Kunlin Wei and Konrad P. K{\"{o}rding}, year={2011} }