Analyzing Human Search Behavior When Subjective Returns are Unobservable

Shinji Nakazato (), Bojian Yang () and Tetsuya Shimokawa ()
Additional contact information
Shinji Nakazato: Tokyo University of Science
Bojian Yang: Tokyo University of Science
Tetsuya Shimokawa: Tokyo University of Science

Computational Economics, 2024, vol. 63, issue 5, No 10, 1947 pages

Abstract: Abstract The exploration versus exploitation dilemma is a critical issue in human information acquisition and sequential belief formation, and the multi-armed bandit problem has been widely used to address it. Because of its high descriptive accuracy, the SGU model, which combines SoftMax type probabilistic selection, Gaussian process regression type belief updating, and upper confidence interval type evaluation, has attracted much attention. However, this model assumes that the analyst has access to the returns from people’s choices, but in many realistic tasks, this assumption cannot be made because only choices are observable. Moreover, many of the returns are subjective. The authors introduce a new model-fitting method that overcomes this barrier and evaluates its performance using data sets derived from agent-based simulations and real consumer data. This approach has the potential to significantly broaden the range of issues to which the SGU model can be applied.

Keywords: Multi-armed-bandit problem; Human exploratory behavior; Gaussian process; Subjective return (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10614-023-10388-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:compec:v:63:y:2024:i:5:d:10.1007_s10614-023-10388-1

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-023-10388-1

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().