Abstract
Co-evolutionary learning is a process where a set of agents mutually adapt via strategic interactions. In this paper, we consider the ability of co-evolutionary learning to evolve cooperative strategies in structured populations using the N-player Iterated Prisoner’s Dilemma (NIPD). To do so, we examine the effects of both fixed and random neighbourhood structures on the evolution of cooperative behaviour in a lattice-based NIPD model. Our main focus is to gain a deeper understanding on how co-evolutionary learning could work well in a spatially structured environment. The numerical experiments demonstrate that, while some recent studies have shown that neighbourhood structures encourage cooperation to emerge, the topological arrangement of the neighbourhood structures is an important factor that determines the level of cooperation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Axelrod, R.: The Evolution of Cooperation. Basic Books, New York (1984)
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 Kaufmann, Los Altos (1987)
Lindgren, K.: Evolution Phenomena in Simple Dynamics. In: Langton, C.G., Taylor, C., Farmer, J.D., Rasmussen, S. (eds.) Artificial Life II: Proceedings of the 2nd Interdisciplinary Workshop on the Synthesis and Simulation of Living Systems, pp. 295–312. Addison-Wesley, Reading (1991)
Fogel, D.B.: Evolving Behaviors in the Iterated Prisoner’s Dilemma. Evolutionary Computation 1(1), 77–97 (1993)
Davis, J.H., Laughlin, P.R., Komorita, S.S.: The Social Psychology of Small Groups. Annual Review of Psychology 27, 501–542 (1976)
Yao, X., Darwen, P.: An Experimental Study of N-person Iterated Prisoner’s Dilemma Games. Informatica 18(4), 435–450 (1994)
Seo, Y.G., Cho, S.B., Yao, X.: The Impact of Payoff Function and Local Interaction on the N-player Iterated Prisoner’s Dilemma. Knowledge and Information Systems: An International Journal 2(4), 178–461 (2000)
Seo, Y.G., Cho, S.B., Yao, X.: Emergence of Cooperative Coalition in NIPD Game with Localization of Interaction and Learning. In: Proceedings of the 1999 Congress on Evolutionary Computation, pp. 877–884. IEEE Press, Piscataway (1999)
Suzuki, R., Arita, T.: Evolutionary Analysis on Spatial Locality in N-Person Iterated Prisoner’s Dilemma. International Journal of Computational Intelligence and Applications 3(2), 177–188 (2003)
Yao, X.: Automatic Acquisition of Strategies by Co-evolutionary Learning. In: Proceedings of the International Conference on Computational Intelligence and Multimedia Applications, Gold Coast, Australia, pp. 23–29. Griffith University Press, Brisbane (1997)
O’Riordan, C., Griffith, J., Newell, J., Sorensen, H.: Co-evolution of Strategies for an N-player Dilemma. In: Proceedings of the 2004 Congress on Evolutionary Computation, pp. 1625–1630. IEEE Press, Piscataway (2004)
Birk, A.: Trust in an N-player Iterated Prisoner’s Dilemma. In: Proceedings of the International Conference on Autonomous Agents, 2nd Workshop on Deception, Fraud and Trust in Agent Societies, Seattle, WA (1999)
O’Riordan, C., Griffith, J., Curran, D., Sorensen, H.: Norms and Cultural Learning in the N-player Prisoner’s Dilemma. In: Proceedings of the 2006 Congress on Evolutionary Computation, pp. 1105–1110. IEEE Press, Piscataway (2006)
Ohtsuki, H., Hauert, C., Lieberman, E., Nowak, M.A.: A Simple Rule for the Evolution of Cooperation on Graphs and Social Networks. Nature 441, 502–505 (2006)
Taylor, P.D., Day, T., Wild, G.: Evolution of Cooperation in a Finite Homogeneous Graph. Nature 447, 469–472 (2007)
Lozano, S., Arenas, A., Sánchez, A.: Mesoscopic Structure Conditions the Emergence of Cooperation on Social Networks. PLoS ONE 3(4), e1892 (2008)
Tarnita, C.E., Antal, T., Ohtsuki, H., Nowak, M.A.: Evolutionary Dynamics in Set Structured Populations. Proceedings of the National Academy of Sciences of the United States of America 106(21), 8601–8604 (2009)
Chiong, R., Dhakal, S., Jankovic, L.: Effects of Neighbourhood Structure on Evolution of Cooperation in N-Player Iterated Prisoner’s Dilemma. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds.) IDEAL 2007. LNCS, vol. 4881, pp. 950–959. Springer, Heidelberg (2007)
O’Riordan, C., Sorensen, H.: Stable Cooperation in the N-Player Prisoner’s Dilemma: The Importance of Community Structure. In: Tuyls, K., Nowé, A., Guessoum, Z., Kudenko, D. (eds.) ALAMAS 2005, ALAMAS 2006, and ALAMAS 2007. LNCS (LNAI), vol. 4865, pp. 157–168. Springer, Heidelberg (2008)
O’Riordan, C., Cunningham, A., Sorensen, H.: Emergence of Cooperation in N-Player Games on Small World Networks. In: Bullock, S., Noble, J., Watson, R., Bedau, M.A. (eds.) Artificial Life XI: Proceedings of the 11th International Conference on the Simulation and Synthesis of Living Systems, pp. 436–442. MIT Press, Cambridge (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chiong, R., Kirley, M. (2009). Co-evolutionary Learning in the N-player Iterated Prisoner’s Dilemma with a Structured Environment. In: Korb, K., Randall, M., Hendtlass, T. (eds) Artificial Life: Borrowing from Biology. ACAL 2009. Lecture Notes in Computer Science(), vol 5865. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10427-5_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-10427-5_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10426-8
Online ISBN: 978-3-642-10427-5
eBook Packages: Computer ScienceComputer Science (R0)