UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Generalization guides human exploration in vast decision spaces

Wu, CM; Schulz, E; Speekenbrink, M; Nelson, JD; Meder, B; (2018) Generalization guides human exploration in vast decision spaces. Nature Human Behaviour , 2 pp. 915-924. 10.1038/s41562-018-0467-4. (In press). Green open access

[thumbnail of Speekenbrink_Generalization guides human exploration in vast decision spaces_AAM.pdf]
Preview
Text
Speekenbrink_Generalization guides human exploration in vast decision spaces_AAM.pdf - Accepted version

Download (28MB) | Preview

Abstract

From foraging for food to learning complex games, many aspects of human behaviour can be framed as a search problem with a vast space of possible actions. Under finite search horizons, optimal solutions are generally unobtainable. Yet, how do humans navigate vast problem spaces, which require intelligent exploration of unobserved actions? Using various bandit tasks with up to 121 arms, we study how humans search for rewards under limited search horizons, in which the spatial correlation of rewards (in both generated and natural environments) provides traction for generalization. Across various different probabilistic and heuristic models, we find evidence that Gaussian process function learning—combined with an optimistic upper confidence bound sampling strategy—provides a robust account of how people use generalization to guide search. Our modelling results and parameter estimates are recoverable and can be used to simulate human-like performance, providing insights about human behaviour in complex environments.

Type: Article
Title: Generalization guides human exploration in vast decision spaces
Open access status: An open access version is available from UCL Discovery
DOI: 10.1038/s41562-018-0467-4
Publisher version: https://doi.org/10.1038/s41562-018-0467-4
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Computational science, Human behaviour
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology
URI: https://discovery.ucl.ac.uk/id/eprint/10062854
Downloads since deposit
445Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item