Title |
Planning and navigation as active inference
|
---|---|
Published in |
Biological Cybernetics, March 2018
|
DOI | 10.1007/s00422-018-0753-2 |
Pubmed ID | |
Authors |
Raphael Kaplan, Karl J. Friston |
Abstract |
This paper introduces an active inference formulation of planning and navigation. It illustrates how the exploitation-exploration dilemma is dissolved by acting to minimise uncertainty (i.e. expected surprise or free energy). We use simulations of a maze problem to illustrate how agents can solve quite complicated problems using context sensitive prior preferences to form subgoals. Our focus is on how epistemic behaviour-driven by novelty and the imperative to reduce uncertainty about the world-contextualises pragmatic or goal-directed behaviour. Using simulations, we illustrate the underlying process theory with synthetic behavioural and electrophysiological responses during exploration of a maze and subsequent navigation to a target location. An interesting phenomenon that emerged from the simulations was a putative distinction between 'place cells'-that fire when a subgoal is reached-and 'path cells'-that fire until a subgoal is reached. |
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Japan | 1 | 11% |
Netherlands | 1 | 11% |
United States | 1 | 11% |
Italy | 1 | 11% |
Unknown | 5 | 56% |
Demographic breakdown
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Members of the public | 6 | 67% |
Scientists | 2 | 22% |
Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
Geographical breakdown
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---|---|---|
Unknown | 204 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 47 | 23% |
Researcher | 38 | 19% |
Student > Master | 28 | 14% |
Student > Bachelor | 19 | 9% |
Student > Doctoral Student | 10 | 5% |
Other | 24 | 12% |
Unknown | 38 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Neuroscience | 36 | 18% |
Engineering | 31 | 15% |
Psychology | 29 | 14% |
Computer Science | 23 | 11% |
Agricultural and Biological Sciences | 9 | 4% |
Other | 25 | 12% |
Unknown | 51 | 25% |