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Characterizing Agent Behavior in Revision Games with Uncertain Deadline

Zhuohan Wang and Dong Hao ()
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Zhuohan Wang: School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610056, China
Dong Hao: School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610056, China

Games, 2022, vol. 13, issue 6, 1-13

Abstract: Revision game is a very recent advance in dynamic game theory and it can be used to analyze the trading in the pre-opening stock market. In such games, players prepare actions that will be implemented at a given deadline, before which they may have opportunities to revise actions. For the first time, we study the role of the deadline in revision games, which is the core component that distinguishes revision games from classic games. We introduce the deadline distribution into revision game model and characterize the sufficient and necessary condition for players’ strategies to constitute an equilibrium. The equilibrium strategy with respect to the deadline uncertainty is given by a simple differential equation set. Governed by this differential equation set, players initially fully cooperate, and the cooperation level decreases as time progresses. The uncertainty has a great impact on players’ behavior. As the uncertainty increases, players become more risk averse, in the sense that they prefer lower mutual cooperation rate rather than higher payoff with higher uncertainty. Specifically, they will not stay in full cooperation for a long time, while after they deviate from the full cooperation, they adjust their plans more slowly and cautiously. The deadline uncertainty can improve the competition and avoid collusion in games, which could be utilized for auction design and pre-opening stock market regulations.

Keywords: revision game; uncertain deadline; stochastic process; multiagent cooperation; pre-opening stock market (search for similar items in EconPapers)
JEL-codes: C C7 C70 C71 C72 C73 (search for similar items in EconPapers)
Date: 2022
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