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Exploitative and Exploratory Attention in a Four-Armed Bandit Task

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Publication date2017
Host publicationCogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition
PublisherThe Cognitive Science Society
Pages3484-3489
Number of pages6
ISBN (electronic)9780991196760
<mark>Original language</mark>English
Event39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017 - London, United Kingdom
Duration: 26/07/201729/07/2017

Conference

Conference39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017
Country/TerritoryUnited Kingdom
CityLondon
Period26/07/1729/07/17

Publication series

NameCogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition

Conference

Conference39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017
Country/TerritoryUnited Kingdom
CityLondon
Period26/07/1729/07/17

Abstract

When making decisions, we are often forced to choose between something safe we have chosen before, and something unknown to us that is inherently risky, but may provide a better long-term outcome. This problem is known as the Exploitation-Exploration (EE) Trade-Off. Most previous studies on the EE Trade-Off have relied on response data, leading to some ambiguity over whether uncertainty leads to true exploratory behavior, or whether the pattern of responding simply reflects a simpler ratio choice rule (such as the Generalized Matching Law (Baum, 1974; Herrnstein, 1961)). Here, we argue that the study of this issue can be enriched by measuring changes in attention (via eye-gaze), with the potential to disambiguate these two accounts. We find that when moving from certainty into uncertainty, the overall level of attention to stimuli in the task increases; a finding we argue is outside of the scope of ratio choice rules.

Bibliographic note

Publisher Copyright: © CogSci 2017.