Evolutionary models of bargaining: comparing agent-based computational and analytical approaches to understanding convention evolution

摘要

This paper compares two methodologies that have been used to understand the evolution of bargaining conventions. The first is the analytical approach that employs a standard learning dynamic and computes equilibria numerically. The second simulates an environment with a finite population of interacting agents. We compare these two approaches within the context of three variations on a common model. In one variation agents randomly experiment with different demands. A second variation posits assortative interactions, and the third allows for sophistication in agent strategies.