Abstract
In classical control systems, the plant to be controlled does not have intention to gain its payoff or benefit, which is obviously not the case in various aspects of social and economic systems(or subsystems). In the latter case, competition and cooperation between players who will optimize their own payoffs turn out to be an important feature, and a fundamental problem is how to achieve cooperation from these rational players. In this paper, we present a neat way to lead to cooperation in dynamical Prisoner’s Dilemma game. In our scenario, the two players are heterogenous with hierarchical roles as the ‘leader’ and the ‘follower’ respectively. It is shown that the system will co-evolve into and stay at the cooperation state if and only if the leader is restricted not to take the dominating strategies. For the special case of 1-step-memory, the optimal strategies for the leader and follower are ‘Tit for Tat’ and ‘ALL C’ respectively. In this framework, both the heterogeneity of the players’ roles and the multiplicity of time-scales are crucial for cooperation, which are quite natural settings from the view point of control theory. Besides, the boundary for cooperation also turns out to depend on the relative
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References
Guo L. Adaptive systems theory: some basic concepts, methods and results. J Syst Sci Complex, 2003, 16: 293–306
Fudenberg D, Tirole J. Game Theory. Cambridge: MIT Press, 1991
Isaacs R. Differential Games: a Mathematical Theory with Applications to Warfare and Pursuit, Control and Optimization. New York: Wiley, 1965
Mu Y, Guo L. Optimization and identification in nonequilibrium dynamical games. In: Proceedings of the 48th IEEE Conference on Decision and Control, Shanghai, 2009. 5750–5755
Axelrod R. The Evolution of Cooperation. New York: Basic Books, 1984
Axelrod R. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. New Jersey: Princeton University Press, 1997
Davis L. Genetic Algorithms and Simulated Annealing. London: Morgan Kaufman Publishers, Inc., 1987
Nowak M A, Bonhoeffer S, May R M. Spatial games and the maintenance of cooperation. Proc Natl Acad Sci USA, 1994, 91: 4877–4881
Ohtsuki H, Hauert C, Lieberman E, et al. A simple rule for the evolution of cooperation on graphs and social networks. Nature, 2006, 441: 502–505
Rubinstein A. Finite automata play the repeated Prisoner’s Dilemma. J Econ Theor, 1986, 39: 83–96
Neyman A, Okada D. Two-person repeated games with finite automata. Int J Game Theory, 2000, 29: 309–325
Radner R. Can bounded rationality resolve the Prisoner’s Dilemma. In: Mas-Colell A, Hildenbrand W, eds. Essays in Honor of Gerard Debreu. Amsterdam: North-Holland, 1986. 387–399
Smale S. The Prisoner’s Dilemma and synamical systems asociated to noncooperative games. Econometrica, 1980, 48: 1617–1634
Nowak M A. Five rules for the evolution of cooperation. Science, 2006, 314: 1560–1563
Kleimenov A F, Semenishchev A A. Repeated Prisoner’s Dilemma: Stackelberg solution with finite memory. In: Proceedings of the 11th IFAC workshop of Control Applications of Optimization, St. Petersburg, 2000, 2: 567–572
Mu Y, Guo L. How cooperation arises from rational players? In: Proceedings of the 49th IEEE Conference on Decision and Control, Atlanta, 2010. 6149–6154
Imhofa L A, Fudenberg D, Nowak M A. Tit-for-tat or win-stay, lose-shift? J Theor Biol, 2007, 247: 574–580
Souzaa M O, Pachecob J M, Santosc F C. Evolution of cooperation under N-person snowdrift games. J Theor Biol, 2009, 260: 581–588
Skyrms B. The Stag Hunt and the Evolution of Social Structure. Cambridge: Cambridge University Press, 2004
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Mu, Y., Guo, L. How cooperation arises from rational players?. Sci. China Inf. Sci. 56, 1–9 (2013). https://doi.org/10.1007/s11432-013-4857-y
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DOI: https://doi.org/10.1007/s11432-013-4857-y