Abstract
This paper compares two methodologies that have been used tounderstand the evolution of bargaining conventions. The first is theanalytical approach that employs a standard learning dynamic andcomputes equilibria numerically. The second approach simulatesan environment with a finite population of interacting agents.We compare these two approaches within the context of threevariations on a common model. In one variation agents randomlyexperiment with different demands. A second variation positsassortative interactions, and the third allows forsophistication in agent strategies. The simulation resultssuggest that the agent-based approach performs well in selectingequilibria in most instances, but exact predicted populationdistributions often vary from those calculated numerically.Classification Numbers: C63, C73, C78.
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Carpenter, J.P. Evolutionary Models of Bargaining: Comparing Agent-based Computational and Analytical Approaches to Understanding Convention Evolution. Computational Economics 19, 25–49 (2002). https://doi.org/10.1023/A:1014936807143
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DOI: https://doi.org/10.1023/A:1014936807143