Open AccessOptimism and pessimism in optimised replay
Author(s) -
Georgy K. Antonov,
Chris Gagne,
Eran Eldar,
Peter Dayan
Publication year - 2022
Publication title -
plos computational biology/plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1009634
Subject(s) - task (project management) , computer science , pessimism , variety (cybernetics) , action (physics) , optimism , prioritization , consolidation (business) , machine learning , artificial intelligence , cognitive psychology , psychology , social psychology , management science , management , accounting , epistemology , quantum mechanics , economics , business , philosophy , physics
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.