Schwartenbeck, P;
Passecker, J;
Hauser, TU;
FitzGerald, TH;
Kronbichler, M;
Friston, KJ;
(2019)
Computational mechanisms of curiosity and goal-directed exploration.
eLife
, 8
, Article e41703. 10.7554/eLife.41703.
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Abstract
Successful behaviour depends on the right balance between maximising reward and soliciting information about the world. Here, we show how different types of information-gain emerge when casting behaviour as surprise minimisation. We present two distinct mechanisms for goal-directed exploration that express separable profiles of active sampling to reduce uncertainty. 'Hidden state' exploration motivates agents to sample unambiguous observations to accurately infer the (hidden) state of the world. Conversely, 'model parameter' exploration, compels agents to sample outcomes associated with high uncertainty, if they are informative for their representation of the task structure. We illustrate the emergence of these types of information-gain, termed active inference and active learning, and show how these forms of exploration induce distinct patterns of 'Bayes-optimal' behaviour. Our findings provide a computational framework for understanding how distinct levels of uncertainty systematically affect the exploration-exploitation trade-off in decision-making.
| Type: | Article |
|---|---|
| Title: | Computational mechanisms of curiosity and goal-directed exploration |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.7554/eLife.41703 |
| Publisher version: | https://doi.org/10.7554/eLife.41703 |
| Language: | English |
| Additional information: | Copyright © 2019, Schwartenbeck et al. This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited. |
| Keywords: | active inference, active learning, curiosity, exploitation, exploration, intrinsic motivation, neuroscience, none |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10074106 |
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