What Drives People's Choices in Turn-Taking Games, if not Game-Theoretic Rationality?

In an earlier experiment, participants played a perfect information game against a computer, which was programmed to deviate often from its backward induction strategy right at the beginning of the game. Participants knew that in each game, the computer was nevertheless optimizing against some belie...

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Main Authors: Sujata Ghosh, Aviad Heifetz, Rineke Verbrugge, Harmen de Weerd
Format: Article
Language:English
Published: Open Publishing Association 2017-07-01
Series:Electronic Proceedings in Theoretical Computer Science
Online Access:http://arxiv.org/pdf/1707.08749v1
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spelling doaj-6b7e9345468849e5bad4794f42278af42020-11-25T02:10:28ZengOpen Publishing AssociationElectronic Proceedings in Theoretical Computer Science2075-21802017-07-01251Proc. TARK 201726528410.4204/EPTCS.251.19:31What Drives People's Choices in Turn-Taking Games, if not Game-Theoretic Rationality?Sujata Ghosh0Aviad Heifetz1Rineke Verbrugge2Harmen de Weerd3 Indian Statistical Institute, Chennai, India The Open University of Israel, Raanana, Israe University of Groningen, Groningen, The Netherlands University of Groningen, Groningen, The Netherlands In an earlier experiment, participants played a perfect information game against a computer, which was programmed to deviate often from its backward induction strategy right at the beginning of the game. Participants knew that in each game, the computer was nevertheless optimizing against some belief about the participant's future strategy. In the aggregate, it appeared that participants applied forward induction. However, cardinal effects seemed to play a role as well: a number of participants might have been trying to maximize expected utility. In order to find out how people really reason in such a game, we designed centipede-like turn-taking games with new payoff structures in order to make such cardinal effects less likely. We ran a new experiment with 50 participants, based on marble drop visualizations of these revised payoff structures. After participants played 48 test games, we asked a number of questions to gauge the participants' reasoning about their own and the opponent's strategy at all decision nodes of a sample game. We also checked how the verbalized strategies fit to the actual choices they made at all their decision points in the 48 test games. Even though in the aggregate, participants in the new experiment still tend to slightly favor the forward induction choice at their first decision node, their verbalized strategies most often depend on their own attitudes towards risk and those they assign to the computer opponent, sometimes in addition to considerations about cooperativeness and competitiveness.http://arxiv.org/pdf/1707.08749v1
collection DOAJ
language English
format Article
sources DOAJ
author Sujata Ghosh
Aviad Heifetz
Rineke Verbrugge
Harmen de Weerd
spellingShingle Sujata Ghosh
Aviad Heifetz
Rineke Verbrugge
Harmen de Weerd
What Drives People's Choices in Turn-Taking Games, if not Game-Theoretic Rationality?
Electronic Proceedings in Theoretical Computer Science
author_facet Sujata Ghosh
Aviad Heifetz
Rineke Verbrugge
Harmen de Weerd
author_sort Sujata Ghosh
title What Drives People's Choices in Turn-Taking Games, if not Game-Theoretic Rationality?
title_short What Drives People's Choices in Turn-Taking Games, if not Game-Theoretic Rationality?
title_full What Drives People's Choices in Turn-Taking Games, if not Game-Theoretic Rationality?
title_fullStr What Drives People's Choices in Turn-Taking Games, if not Game-Theoretic Rationality?
title_full_unstemmed What Drives People's Choices in Turn-Taking Games, if not Game-Theoretic Rationality?
title_sort what drives people's choices in turn-taking games, if not game-theoretic rationality?
publisher Open Publishing Association
series Electronic Proceedings in Theoretical Computer Science
issn 2075-2180
publishDate 2017-07-01
description In an earlier experiment, participants played a perfect information game against a computer, which was programmed to deviate often from its backward induction strategy right at the beginning of the game. Participants knew that in each game, the computer was nevertheless optimizing against some belief about the participant's future strategy. In the aggregate, it appeared that participants applied forward induction. However, cardinal effects seemed to play a role as well: a number of participants might have been trying to maximize expected utility. In order to find out how people really reason in such a game, we designed centipede-like turn-taking games with new payoff structures in order to make such cardinal effects less likely. We ran a new experiment with 50 participants, based on marble drop visualizations of these revised payoff structures. After participants played 48 test games, we asked a number of questions to gauge the participants' reasoning about their own and the opponent's strategy at all decision nodes of a sample game. We also checked how the verbalized strategies fit to the actual choices they made at all their decision points in the 48 test games. Even though in the aggregate, participants in the new experiment still tend to slightly favor the forward induction choice at their first decision node, their verbalized strategies most often depend on their own attitudes towards risk and those they assign to the computer opponent, sometimes in addition to considerations about cooperativeness and competitiveness.
url http://arxiv.org/pdf/1707.08749v1
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