This article presents the evolutionary dynamics of three games: the Nash bargaining game, the ultimatum game, and a hybrid of the two. One might expect that the probability that some behavior evolves in an environment with two games would be near the probability that the same behavior evolves in either game alone. This is not the case for the ultimatum and Nash bargaining games. Fair behavior is more likely to evolve in a combined game than in either game taken individually. (...) This result confirms a conjecture that the complexity of our actual environment provides an explanation for the evolution of fair behavior. Key Words: evolutionary game theory • Nash bargaining game • ultimatum game • fairness. (shrink)

Abstract:I examine from a conventionalist perspective the Nash bargaining problem that philosophers use as a tool for analyzing fair division. From this perspective, the solutions to bargaining problems are conventions that can emerge from inductive learning and focal point effects. I contrast the conventionalist approach to analyzing the bargaining problem with the better-known rational choice approach, which I criticize for having overly demanding epistemic presuppositions and for producing disappointing results. I apply a simple model of inductive learning to specific bargaining (...) problems to show that agents can learn from repeated experience to follow a variety of bargaining conventions in a given problem. I conclude that such agents can come to regard two such conventions as focal for the bargaining problem, one that assigns claimants equal shares of a good and another egalitarian solution of equal payoff gains, and that the egalitarian solution tends to prevail when these two solutions differ. I conclude further that the above analysis lends support for admitting interpersonal utility comparisons into the analysis of fair division problems, and also suggests a focal point explanation of the wide acceptance of the Aristotelian proportionality principle of distributive justice. (shrink)