On the Structural Robustness of Evolutionary Models of Cooperation
This paper studies the structural robustness of evolutionary models of cooperation, i.e. their sensitivity to small structural changes. To do this, we focus on the Prisoner’s Dilemma game and on the set of stochastic strategies that are conditioned on the last action of the player’s opponent. Strategies such as Tit-For-Tat (TFT) and Always-Defect (ALLD) are particular and classical cases within this framework; here we study their potential appearance and their evolutionary robustness, as well as the impact of small changes in the model parameters on their evolutionary dynamics. Our results show that the type of strategies that are likely to emerge and be sustained in evolutionary contexts is strongly dependent on assumptions that traditionally have been thought to be unimportant or secondary (number of players, mutation-rate, population structure...). We find that ALLD-like strategies tend to be the most successful in most environments, and we also discuss the conditions that favor the appearance of TFTlike strategies and cooperation.
KeywordsEvolution of Cooperation Evolutionary Game Theory Iterated Prisoner’s Dilemma Tit for Tat Agent-based Modeling
Unable to display preview. Download preview PDF.
- Axelrod, R.: The Evolution of Cooperation. Basic Books USA (1984)Google Scholar
- Axelrod, R.: The Evolution of Strategies in the Iterated Prisoner’s Dilemma. In: Davis, L. (ed.) Genetic Algorithms and Simulated Annealing, pp. 32–41. Morgan Kaufman, San Francisco (1987); Reprinted in Axelrod, R.: The complexity of cooperation. Agent-based models of competition and collaboration. Princeton University Press, Princeton (1997)Google Scholar
- Binmore, K.: Playing Fair: Game Theory and the Social Contract I. MIT Press, Cambridge (1994)Google Scholar
- Binmore, K.: Review of the book: The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. In: Axelrod, R. (ed.), Princeton University Press, Princeton (1997); Journal of Artificial Societies and Social Simulation 1(1) (1998), http://jasss.soc.surrey.ac.uk/1/1/review1.html
- Probst, D.: On Evolution and Learning in Games. PhD thesis, University of Bonn (1996)Google Scholar
- Wilensky, U.: NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL (1999), http://ccl.northwestern.edu/netlogo/
- Kulkarni, V.G.: Modelling and Analysis of Stochastic Systems. Chapman & Hall/CRC (1995)Google Scholar