Carvalho, Wilka;
Tomov, Momchil S;
de Cothi, William;
Barry, Caswell;
Gershman, Samuel J;
(2024)
Predictive Representations: Building Blocks of Intelligence.
Neural Computation
pp. 1-74.
10.1162/neco_a_01705.
(In press).
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Abstract
Adaptive behavior often requires predicting future events. The theory of reinforcement learning prescribes what kinds of predictive representations are useful and how to compute them. This review integrates these theoretical ideas with work on cognition and neuroscience. We pay special attention to the successor representation and its generalizations, which have been widely applied as both engineering tools and models of brain function. This convergence suggests that particular kinds of predictive representations may function as versatile building blocks of intelligence.
| Type: | Article |
|---|---|
| Title: | Predictive Representations: Building Blocks of Intelligence |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1162/neco_a_01705 |
| Publisher version: | http://dx.doi.org/10.1162/neco_a_01705 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| 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 Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Cell and Developmental Biology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10196628 |
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