Runtime Bounds for a Coevolutionary Algorithm on Classes of Potential Games
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3729878.3746616.pdf
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750.16 KB
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Author(s)
Hevia Fajardo, Mario Alejandro
Toutouh, Jamal
Hemberg, Erik
O'Reilly, Una-May
Lehre, Per Kristian
Publisher
ACM|Foundations of Genetic Algorithms XVIII
Citation
Mario Hevia Fajardo, Jamal Toutouh, Erik Hemberg, Una-May O'Reilly, and Per Kristian Lehre. 2025. Runtime Bounds for a Coevolutionary Algorithm on Classes of Potential Games. In Proceedings of the 18th ACM/SIGEVO Conference on Foundations of Genetic Algorithms (FOGA '25). Association for Computing Machinery, New York, NY, USA, 85–95.
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Final published version
Abstract
Coevolutionary algorithms are a family of black-box optimisation algorithms with many applications in game theory. We study a coevolutionary algorithm on an important class of games in game theory: potential games. In these games, a real-valued function defined over the entire strategy space encapsulates the strategic choices of all players collectively. We present the first theoretical analysis of a coevolutionary algorithm on potential games, showing a runtime guarantee that holds for all exact potential games, some weighted and ordinal potential games, and certain non-potential games. Using this result, we show a polynomial runtime on singleton congestion games. Furthermore, we show that there exist games for which coevolutionary algorithms find Nash equilibria exponentially faster than best or better response dynamics, and games for which coevolutionary algorithms find better Nash equilibria as well. Finally, we conduct experimental evaluations showing that our algorithm can outperform widely used algorithms, such as better response on random instances of singleton congestion games, as well as fictitious play, counterfactual regret minimisation (CFR), and external sampling CFR on dynamic routing games.
Description
FOGA ’25, Leiden, Netherlands
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1145/3729878.3746616
