PT  - JOURNAL ARTICLE
AU  - Samuel J. Gershman
TI  - Origin of perseveration in the trade-off between reward and complexity
AID  - 10.1101/2020.01.16.903476
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.01.16.903476
4099  - http://biorxiv.org/content/early/2020/01/16/2020.01.16.903476.short
4100  - http://biorxiv.org/content/early/2020/01/16/2020.01.16.903476.full
AB  - When humans and other animals make repeated choices, they tend to repeat previously chosen actions independently of their reward history. This paper locates the origin of perseveration in a trade-off between two computational goals: maximizing rewards and minimizing the complexity of the action policy. We develop an information-theoretic formalization of policy complexity and show how optimizing the trade-off leads to perseveration. Analysis of two data sets reveals that people attain close to optimal trade-offs. Parameter estimation and model comparison supports the claim that perseveration quantitatively agrees with the theoretically predicted functional form.