Bayesian Models of Brain and Behaviour

<table>Planning as forward and backwards inference over states and controls. Planning can be formulated as estimation of a density over actions <svg height="16.5625" id="M152" style="vertical-align:-3.50804pt" version="1.1" viewbox="0 0 104.9875 16.5625" width="104.9875" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg> given current state <svg height="11.825" id="M153" style="vertical-align:-3.27605pt" version="1.1" viewbox="0 0 15.9625 11.825" width="15.9625" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg> and desired sensory consequences, <svg height="15.35" id="M154" style="vertical-align:-3.3525pt" version="1.1" viewbox="0 0 22.6875 15.35" width="22.6875" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg>.</table>

International Scholarly Research Notices

Bayesian Models of Brain and Behaviour

Figure 7