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Evolutionary Game Theory: A General Review

Author

Listed:
  • Aras YOLUSEVER

    (Department of Economics, Faculty of Economics and Administrative Sciences, Istanbul Kultur University, İstanbul, Türkiye)

Abstract

This article surveys the Evolutionary Game Theory (now EGT), encompassing its historical underpinnings, recent advancements, and future potential. Originating in the 1970s through the pioneering work of John Maynard Smith and George R. Price, EGT leverages game-the-oretic concepts to elucidate the evolution of strategies within various populations across biological, economic, and social domains. Notably, recent progress has seen the integration of advanced large language models (LLMs) such as GPT-3.5 and GPT-4 into agent-based simulations, thereby enriching the authenticity and intricacy of strategic interactions. Additionally, the study addresses the complexities associated with modeling diverse behaviors and bridging the insights derived from LLMs to practical applications in fields like biology, healthcare, education, and social sciences. Moreover, it highlights the importance of interdisciplinary collaboration and innovative methodologies in tackling the complex challenges associated with EGT. The article also reflects on potential directions for future research, stressing the integration of EGT with practical applications and the need for comprehensive models that capture the intricacies of evolutionary dynamics in adaptive systems.

Suggested Citation

  • Aras YOLUSEVER, 2024. "Evolutionary Game Theory: A General Review," Yildiz Social Science Review, Yildiz Technical University, vol. 10(2), pages 85-98, December .
    • Handle: RePEc:aye:journl:v:10:y:2024:i:2:p:85-98
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    References listed on IDEAS

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    1. Benjamin Wölfl & Hedy te Rietmole & Monica Salvioli & Artem Kaznatcheev & Frank Thuijsman & Joel S. Brown & Boudewijn Burgering & Kateřina Staňková, 2022. "The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer," Dynamic Games and Applications, Springer, vol. 12(2), pages 313-342, June.
    2. Anuraag Bukkuri & Joel S. Brown, 2021. "Evolutionary Game Theory: Darwinian Dynamics and the G Function Approach," Games, MDPI, vol. 12(4), pages 1-19, September.
    3. Alger, Ingela & Weibull, Jörgen W., 2016. "Evolution and Kantian morality," Games and Economic Behavior, Elsevier, vol. 98(C), pages 56-67.
    4. Shleifer, Andrei, 2000. "Inefficient Markets: An Introduction to Behavioral Finance," OUP Catalogue, Oxford University Press, number 9780198292272.
    5. Yanwei You & Yuquan Chen & Yujun You & Qi Zhang & Qiang Cao, 2023. "Evolutionary Game Analysis of Artificial Intelligence Such as the Generative Pre-Trained Transformer in Future Education," Sustainability, MDPI, vol. 15(12), pages 1-12, June.
    6. Mielke, Jahel & Steudle, Gesine A., 2018. "Green Investment and Coordination Failure: An Investors' Perspective," Ecological Economics, Elsevier, vol. 150(C), pages 88-95.
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    More about this item

    Keywords

    Agent-based models; evolutionary game theory; large language models; replicator dynamicsJournal: Yildiz Social Science Review;
    All these keywords.

    JEL classification:

    • F00 - International Economics - - General - - - General
    • F30 - International Economics - - International Finance - - - General
    • G00 - Financial Economics - - General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • K00 - Law and Economics - - General - - - General (including Data Sources and Description)
    • K20 - Law and Economics - - Regulation and Business Law - - - General
    • M00 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General - - - General
    • M20 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - General
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General

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