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Evolutionary dynamics in multitasking environments

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  • Sawa, Ryoji
  • Zusai, Dai

Abstract

We formulate the best response dynamic in a multitasking environment; while agents engage in multiple games concurrently, an agent can switch her action in only one of the games upon receipt of a revision opportunity. The choice of the game in which to revise an action makes the multitasking dynamic behave differently from standard evolutionary dynamics. The timing of revisions in a game becomes endogenous, which causes the transition of the action distribution in each game to depend on those in other games. Despite such complexity, we verify the global stability of the Nash equilibrium set in potential and contractive games as well as the local stability of a regular evolutionary stable state. We also show that the equilibrium to which the multitasking dynamic converges may depend on the task choice rules.

Suggested Citation

  • Sawa, Ryoji & Zusai, Dai, 2019. "Evolutionary dynamics in multitasking environments," Journal of Economic Behavior & Organization, Elsevier, vol. 166(C), pages 288-308.
    • Handle: RePEc:eee:jeborg:v:166:y:2019:i:c:p:288-308
    DOI: 10.1016/j.jebo.2019.06.021
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    1. Srinivas Arigapudi & Omer Edhan & Yuval Heller & Ziv Hellman, 2022. "Mentors and Recombinators: Multi-Dimensional Social Learning," Papers 2205.00278, arXiv.org, revised Nov 2023.

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    More about this item

    Keywords

    Evolution; Multitasking; Bounded rationality; Best response dynamics; Evolutionary stable state; Stability of the Nash equilibrium;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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