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Trait-Augmented Games with Limited-Skill Agents

Author

Listed:
  • Michael Gmeiner

    (Northwestern University, 2211 Campus Drive, 3rd Floor, Evanston, IL, 60208, USA)

  • Val Lambson

    (��Brigham Young University, 2146 West View Building, Provo, UT, 84602, USA)

Abstract

We present a framework populated by limited-skill agents whose cognitive abilities fall short of full rationality in two ways. First, the agents are incapable of considering all of the available actions. Second, they do not perceive the actions directly, but only view traits that are related to the actions’ identities. We define skill in terms of the number of action-trait pairs an agent can consider: agents with higher skill can consider more pairs. Limited-skill agents can be grafted into many contexts. We first discuss trends in how agents select which action-trait pairs to view when maximizing expected payoff. We then present two applications: the relationship between skill and expected payoff and product differentiation.

Suggested Citation

  • Michael Gmeiner & Val Lambson, 2021. "Trait-Augmented Games with Limited-Skill Agents," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 23(03), pages 1-31, September.
    • Handle: RePEc:wsi:igtrxx:v:23:y:2021:i:03:n:s0219198921500043
    DOI: 10.1142/S0219198921500043
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    More about this item

    Keywords

    Bounded rationality; information; skill; product differentiation; constant-sum games;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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