dc.contributor.author
Horvath, Lilla
dc.contributor.author
Colcombe, Stanley
dc.contributor.author
Milham, Michael
dc.contributor.author
Ray, Shruti
dc.contributor.author
Schwartenbeck, Philipp
dc.contributor.author
Ostwald, Dirk
dc.date.accessioned
2023-03-29T11:24:40Z
dc.date.available
2023-03-29T11:24:40Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/38651
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-38367
dc.description.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.
en
dc.format.extent
21 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
Bandit problem
en
dc.subject
Agent-based behavioral modeling
en
dc.subject
Exploitation
en
dc.subject.ddc
100 Philosophie und Psychologie::150 Psychologie::150 Psychologie
dc.title
Human Belief State-Based Exploration and Exploitation in an Information-Selective Symmetric Reversal Bandit Task
dc.type
Wissenschaftlicher Artikel
dc.date.updated
2023-03-27T17:45:44Z
dcterms.bibliographicCitation.doi
10.1007/s42113-021-00112-3
dcterms.bibliographicCitation.journaltitle
Computational Brain & Behavior
dcterms.bibliographicCitation.number
4
dcterms.bibliographicCitation.originalpublishername
Springer International Publishing
dcterms.bibliographicCitation.pagestart
442
dcterms.bibliographicCitation.pageend
462
dcterms.bibliographicCitation.volume
4
dcterms.bibliographicCitation.url
https://doi.org/10.1007/s42113-021-00112-3
refubium.affiliation
Erziehungswissenschaft und Psychologie
refubium.affiliation.other
Arbeitsbereich Computational Cognitive Neuroscience
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.issn
2522-0861
dcterms.isPartOf.eissn
2522-087X
refubium.resourceType.provider
DeepGreen