Finding Core Members of Cooperative Games Using Agent-Based Modeling

Document Type

Article

Publication Date

2021

DOI

10.18564/jasss.4457

Publication Title

Journal of Artificial Societies and Social Simulation

Volume

24

Issue

1

Pages

21 pp.

Abstract

Agent-based modeling (ABM) is a powerful paradigm to gain insight into social phenomena. One area that ABM has rarely been applied is coalition formation. Traditionally, coalition formation is modelled using cooperative game theory. In this paper, a heuristic algorithm, which can be embedded into an ABM to allow the agents to find a coalition, is described. Our heuristic algorithm combines agent-based modeling and cooperative game theory to help find agent partitions that are members of a games' core solutions (if they exist). The accuracy of our heuristic algorithm can be determined by comparing its outcomes to the actual core solutions. This comparison is achieved by developing an experiment that uses a specific example of a cooperative game called the glove game. The glove game is a type of market economy game. Finding the traditional cooperative game solutions is computationally intensive for large numbers of players because each possible partition must be compared to each possible coalition to determine the core set; hence our experiment only considers up to nine-player games. The results indicate that our heuristic approach achieves a core solution over 90% of the games considered in our experiment.

Comments

© Copyright JASSS 2021

Publisher's version available at:

https://doi.org/10.18564/jasss.4457

ORCID

0000-0002-8012-2272 (Collins)

Original Publication Citation

Vernon-Bido, D., & Collins, A. (2021). Finding core members of cooperative games using agent-based modeling. Journal of Artificial Societies and Social Simulation, 24(1), 21 pp., Article 6. https://doi.org/10.18564/jasss.4457

Link to Full Text

Share

COinS