Human Belief State-Based Exploration and Exploitation in an Information-Selective Symmetric Reversal Bandit Task
Document Type
Article
Publication Date
12-1-2021
Abstract
Humans often face sequential decision-making problems, in which information about the environmental reward structure is detached from rewards for a subset of actions. In the current exploratory study, we introduce an information-selective symmetric reversal bandit task to model such situations and obtained choice data on this task from 24 participants. To arbitrate between different decision-making strategies that participants may use on this task, we developed a set of probabilistic agent-based behavioral models, including exploitative and explorative Bayesian agents, as well as heuristic control agents. Upon validating the model and parameter recovery properties of our model set and summarizing the participants’ choice data in a descriptive way, we used a maximum likelihood approach to evaluate the participants’ choice data from the perspective of our model set. In brief, we provide quantitative evidence that participants employ a belief state-based hybrid explorative-exploitative strategy on the information-selective symmetric reversal bandit task, lending further support to the finding that humans are guided by their subjective uncertainty when solving exploration-exploitation dilemmas.
Identifier
85112379797 (Scopus)
Publication Title
Computational Brain and Behavior
External Full Text Location
https://doi.org/10.1007/s42113-021-00112-3
e-ISSN
2522087X
First Page
442
Last Page
462
Issue
4
Volume
4
Recommended Citation
Horvath, Lilla; Colcombe, Stanley; Milham, Michael; Ray, Shruti; Schwartenbeck, Philipp; and Ostwald, Dirk, "Human Belief State-Based Exploration and Exploitation in an Information-Selective Symmetric Reversal Bandit Task" (2021). Faculty Publications. 3642.
https://digitalcommons.njit.edu/fac_pubs/3642