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  Optimism and Pessimism in Optimised Replay

Antonov, G., Gagne, C., Eldar, E., & Dayan, P. (2022). Optimism and Pessimism in Optimised Replay. PLoS Computational Biology, 18(1). doi:10.1101/2021.04.27.441454.

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 Creators:
Antonov, G1, 2, Author           
Gagne, C1, 2, Author           
Eldar, E, Author
Dayan, P1, 2, Author           
Affiliations:
1Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3017468              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: The replay of task-relevant trajectories is known to contribute to memory consolidation and improved task performance. A wide variety of experimental data show that the content of replayed sequences is highly specific and can be modulated by reward as well as other prominent task variables. However, the rules governing the choice of sequences to be replayed still remain poorly understood. One recent theoretical suggestion is that the prioritization of replay experiences in decision-making problems is based on their effect on the choice of action. We show that this implies that subjects should replay sub-optimal actions that they dysfunctionally choose rather than optimal ones, when, by being forgetful, they experience large amounts of uncertainty in their internal models of the world. We use this to account for recent experimental data demonstrating exactly pessimal replay, fitting model parameters to the individual subjects’ choices.

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 Dates: 2022-01
 Publication Status: Published online
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 Rev. Type: -
 Identifiers: DOI: 10.1101/2021.04.27.441454
eDoc: e1009634
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Title: PLoS Computational Biology
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: 32 Volume / Issue: 18 (1) Sequence Number: - Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1