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Intelligent Players in a Fictitious Play Framework
Carnegie Mellon Univ, Robot Inst, Pittsburgh, PA 15213 USA..
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0001-5983-0875
Purdue Univ, Elmore Family Sch Elect & Comp Engn, W Lafayette, IN 47906 USA..
Georgia Inst Technol, Sch Aerosp Engn, Atlanta, GA USA..ORCID iD: 0000-0003-1978-4848
2024 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 69, no 1, p. 479-486Article in journal (Refereed) Published
Abstract [en]

Fictitious play is a popular learning algorithm in which players that utilize the history of actions played by the players and the knowledge of their own payoff matrix can converge to the Nash equilibrium under certain conditions on the game. We consider the presence of an intelligent player that has access to the entire payoff matrix for the game. We show that by not conforming to fictitious play, such a player can achieve a better payoff than the one at the Nash Equilibrium. This result can be viewed both as a fragility of the fictitious play algorithm to a strategic intelligent player and an indication that players should not throw away additional information they may have, as suggested by classical fictitious play.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024. Vol. 69, no 1, p. 479-486
Keywords [en]
Games, IP networks, Nash equilibrium, Convergence, Absorption, Trajectory, Standards, Fragility of algorithms, learning in games, multi-agent systems
National Category
Economics and Business
Identifiers
URN: urn:nbn:se:kth:diva-344472DOI: 10.1109/TAC.2023.3266505ISI: 001163003600020Scopus ID: 2-s2.0-85153359145OAI: oai:DiVA.org:kth-344472DiVA, id: diva2:1845230
Note

QC 20240318

Available from: 2024-03-18 Created: 2024-03-18 Last updated: 2024-03-18Bibliographically approved

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Kanellopoulos, Aris

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  • de-DE
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  • en-US
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Output format
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