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Evolution of Coordination Through Institutional Incentives: An Evolutionary Game Theory Approach

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Abstract

There is a broad recognition that commitment-based mechanisms can promote coordination and cooperative behaviours in both biological populations and self-organised multi-agent systems by making individuals' intentions explicit prior to engagement. Yet their effectiveness depends on sustained compliance supported by institutions, especially in one-off interactions. Despite advances in quantitative studies of cooperation and commitment, most applied analyses and policy debates remain largely qualitative, with limited attention to the allocation of scarce institutional resources between enhancing participation and ensuring commitment compliance. Herein, we develop an evolutionary game-theoretic model that explicitly examines the strategic distribution of a limited budget for institutional incentives, namely rewards or punishments, aimed at these two critical objectives within pre-commitment frameworks. Our findings reveal that a reward-based incentive approach consistently yields greater coordination success than a punishment-based approach, with optimal outcomes arising when resources are appropriately distributed between participation promotion and compliance assurance. These findings offer novel insights for designing institutional incentives to promote broad, coordinated adoption of new technologies.

Original languageEnglish
Title of host publicationProceedings of 2025 7th International Conference on Distributed Artificial Intelligence, DAI 2025
PublisherAssociation for Computing Machinery, Inc
Pages38-47
Number of pages10
ISBN (Electronic)9798400722752
DOIs
Publication statusPublished - 23 Dec 2025
Event2025 7th International Conference on Distributed Artificial Intelligence, DAI 2025 - London, United Kingdom
Duration: 21 Nov 202524 Nov 2025

Conference

Conference2025 7th International Conference on Distributed Artificial Intelligence, DAI 2025
Country/TerritoryUnited Kingdom
CityLondon
Period21/11/2524/11/25

Bibliographical note

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© 2025 Copyright held by the owner/author(s).

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