Centralized versus personalized commitments and their influence on cooperation in group interactions

The Anh Han, Lúis Moniz Pereira, Luis A. Martinez-Vaquero, Tom Lenaerts

Research output: Chapter in Book/Report/Conference proceedingConference paperResearch

13 Citations (Scopus)


Before engaging in a group venture agents may seek commitments from other members in the group and, based on the level of participation (i.e. the number of actually committed participants), decide whether it is worth joining the venture. Alternatively, agents can delegate this costly process to a (beneficent or non-costly) third-party, who helps seek commitments from the agents. Using methods from Evolutionary Game Theory, this paper shows that, in the context of Public Goods Game, much higher levels of cooperation can be achieved through such centralized commitment management. It provides a more efficient mechanism for dealing with commitment free-riders, those who are not willing to bear the cost of arranging commitments whilst enjoying the benefits provided by the paying commitment proposers. We show also that the participation level plays a crucial role in the decision of whether an agreement should be formed; namely, it needs to be more strict in the centralized system for the agreement to be formed; however, once it is done right, it is much more beneficial in terms of the level of cooperation as well as the attainable social welfare. In short, our analysis provides important insights for the design of multi-agent systems that rely on commitments to monitor agents' cooperative behavior.

Original languageEnglish
Title of host publicationproceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI)
PublisherAAAI Press
Number of pages7
ISBN (Electronic)2374-3468
ISBN (Print)2159-5399
Publication statusPublished - 2017
Event31st AAAI Conference on Artificial Intelligence, AAAI 2017 - San Francisco, United States
Duration: 4 Feb 201710 Feb 2017


Conference31st AAAI Conference on Artificial Intelligence, AAAI 2017
Country/TerritoryUnited States
CitySan Francisco


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