Abstract
In this article we tackle the problem of maximizing cooperation among self-interested agents in a resource exchange environment. Our main concern is the design of mechanisms for maximizing cooperation among self-interested agents in a way that their profits increase by exchanging or trading with resources. Although dynamic coalition formation and partner switching (rewiring) have been shown to promote the emergence and maintenance of cooperation for self-interested agents, no prior work in the literature has investigated whether merging both mechanisms exhibits positive synergies that lead to increase cooperation even further. Therefore, we introduce and analyze a novel dynamic coalition formation mechanism, that uses partner switching, to help self-interested agents to increase their profits in a resource exchange environment. Our experiments show the effectiveness of our mechanism at increasing the agents’ profits, as well as the emergence of trading as the preferred behavior over different types of complex networks.
- Adamic, L. A. and Huberman, B. A. 2000. Power-law distribution of the World Wide Web. Science 287, 5461, 2115.Google Scholar
Cross Ref
- Aumann, R. J. 1959. Acceptable points in general cooperative n-person games. In Contribution to the Theory of Game IV, Annals of Mathematical Study 40, R. D. Luce and A. W. Tucker Eds., University Press, 287--324.Google Scholar
- Axelrod, R. 1997. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration 1st Ed. Princeton University Press.Google Scholar
- Axelrod, R. M. 1984. The Evolution of Cooperation. Basic Books, New York.Google Scholar
- Aziz, H., Brandt, F., and Seedig, H. G. 2011. Stable partitions in additively separable hedonic games. In Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’11). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 183--190. Google Scholar
Digital Library
- Bachrach, Y. and Rosenschein, J. S. 2008. Coalitional skill games. In Proceedings of the 7th International Joint Conference on Autonomous agents and Multiagent Systems (AAMAS’08). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 1023--1030. Google Scholar
Digital Library
- Batagelj, V. and Mrvar, A. 2003. Pajek - Analysis and visualization of large networks. In Proceedings of the 9th International Symposium on Graph Drawing. Lecture Notes in Computer Science, vol. 2265, 77--103.Google Scholar
- Bazzan, A., Peleteiro, A., and Burguillo, J. 2011. Learning to cooperate in the iterated prisoner’s dilemma by means of social attachments. J. Braz. Comp. Soc. 17, 3, 163--174.Google Scholar
Cross Ref
- Brandt, F., Conitzer, V., and Endriss, U. 2013. Computational social choice. In Multiagent Systems, G. Weiss Ed., MIT Press, 213--283.Google Scholar
- Burguillo, J. and Peleteiro, A. 2010. Ownership and trade in spatial evolutionary memetic games. In Proceedings of the 11th International Conference on Parallel Problem Solving from Nature (PPSN’10). Springer, 455--464. Google Scholar
Digital Library
- Burguillo-Rial, J. 2009. A memetic framework for describing and simulating spatial prisoner’s dilemma with coalition formation. In Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’09). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 441--448. Google Scholar
Digital Library
- Chalkiadakis, G., Elkind, E., Markakis, E., Polukarov, M., and Jennings, N. 2010. Cooperative games with overlapping coalitions. J. Artif. Intell. Research 39, 179--216. Google Scholar
Digital Library
- Chevaleyre, Y., Endriss, U., Lang, J., and Maudet, N. 2007. A short introduction to computational social choice. In Proceedings of the 33rd Conference on Current Trends in Theory and Practice of Computer Science. J. van Leeuwen, G. F. Italiano, W. van der Hoek, C. Meinel, H. Sack, and F. Plasil Eds., Lecture Notes in Computer Science, vol. 4362, Springer, 51--69. Google Scholar
Digital Library
- Doran, J. E., Franklin, S., Jennings, N. R., and Norman, T. J. 1997. On cooperation in multi-agent systems. Knowledge Engin. Rev. 12, 309--314. Google Scholar
Digital Library
- Eguiluz, V. M., Zimmermann, M. G., Cela-Conde, C. J., and San Miguel, M. 2005. Cooperation and the emergence of role differentiation in the dynamics of social networks. Amer. J. Sociol. 110, 4, 977.Google Scholar
Cross Ref
- Fu, F., Wu, T., and Wang, L. 2009. Partner switching stabilizes cooperation in coevolutionary prisoner’s dilemma. Phys. Rev. E 79, 3, 036101.Google Scholar
Cross Ref
- Fu, F., Tarnita, C. E., Christakis, N. A., Wang, L., Rand, D. G., and Nowak, M. A. 2012. Evolution of in-group favoritism. Scientific Rep. 2, 480.Google Scholar
- Griffiths, N. and Luck, M. 2010. Changing neighbours: Improving tag-based cooperation. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’10). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 249--256. Google Scholar
Digital Library
- Gross, T. and Blasius, B. 2008. Adaptive coevolutionary networks: A review. J. R. Soc. Interface 5, 20, 259--271.Google Scholar
Cross Ref
- Hogg, T. 1995. Social dilemmas in computational ecosystems. In Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI’95). Morgan Kaufmann, San Mateo, CA, 711--716. Google Scholar
Digital Library
- Jackson, M. O., Demange, G., Goyal, S., and Nouwel, A. V. D. 2003. A survey of models of network formation: Stability and efficiency. In Group Formation in Economics: Networks, Clubs and Coalitions, Cambridge University Press.Google Scholar
- Kniesburges, S., Koutsopouplos, A., and Scheideler, C. 2012. A self-stabilization process for small-world networks. In Proceedings of the 26th IEEE International Parallel and Distributed Processing Symposium. 1261--1271. Google Scholar
Digital Library
- Langer, P., Nowak, M., and Hauert, C. 2008. Spatial invasion of cooperation. J. Theor. Biol. 250, 4, 634--641.Google Scholar
Cross Ref
- Maynard Smith, J. and Price, G. R. 1973. The logic of animal conflict. Nature 246, 5427, 15--18.Google Scholar
- Narendra, K. S. and Thathachar, M. A. L. 1989. Learning Automata: An Introduction. Prentice-Hall, Inc., Upper Saddle River, NJ. Google Scholar
Digital Library
- Newman, M. E. J. 2003. The structure and function of complex networks. SIAM Rev. 45, 2, 167--256.Google Scholar
Digital Library
- Nguyen, D.-T. and Ishida, Y. 2009. Spatial dilemma strategies of intelligent agents: Coalition formation in environmental game. In Proceedings of the International Conference on Knowledge and Systems Engineering (KSE’09). IEEE, 126--129. Google Scholar
Digital Library
- Nowak, M. A. and May, R. M. 1992. Evolutionary games and spatial chaos. Nature 359, 6398, 826--829.Google Scholar
- Nowak, M. A. and May, R. M. 1993. The spatial dilemmas of evolution. Int. J. Bifurcation Chaos 3, 1, 35--78.Google Scholar
Cross Ref
- Ostrom, E. 1990. Governing the Commons: The Evolution of Institutions for Collective Action. Political Economy of Institutions and Decisions, Cambridge University Press.Google Scholar
- Pacheco, J. M., Traulsen, A., and Nowak, M. A. 2006. Coevolution of strategy and structure in complex networks with dynamical linking. Phys. Rev. Lett. 97, 25, 258103+.Google Scholar
Cross Ref
- Pastor-Satorras, R. and Vespignani, A. 2001. Epidemic dynamics and endemic states in complex networks. Phys. Rev. E 63, 066117.Google Scholar
Cross Ref
- Peleteiro, A., Burguillo, J., and Bazzan, A. 2011. Emerging cooperation in the spatial IPD with reinforcement learning and coalitions. In Intelligent Decision Systems in Large-Scale Distributed Environment, Studies in Computational Intelligence, Springer.Google Scholar
- Peleteiro, A., Burguillo, J., and Bazzan, A. 2012. How coalitions enhance cooperation in the IPD over complex networks. In Proceedings of the 3rd Brazilian Workshop on Social Simulation. IEEE. Google Scholar
Digital Library
- Perc, M. and Szolnoki, A. 2010. Coevolutionary games--A mini review. Biosystems 99, 2, 109--125.Google Scholar
Cross Ref
- Pitt, J., Schaumeier, J., and Artikis, A. 2011. The axiomatisation of socio-economic principles for self-organising systems. In Proceedings of the IEEE 6th International Conference on Self-Adaptive and Self-Organizing Systems. 138--141. Google Scholar
Digital Library
- Pitt, J., Schaumeier, J., and Artikis, A. 2012a. Axiomatization of socio-economic principles for self-organizing institutions: Concepts, experiments and challenges. ACM Trans. Auton. Adapt. Syst. 7, 4, Article 39. Google Scholar
Digital Library
- Pitt, J., Schaumeier, J., Busquets, D., and Macbeth, S. 2012b. Self-organising common-pool resource allocation and canons of distributive justice. In Proceedings of the IEEE 6th International Conference on Self-Adaptive and Self-Organizing Systems. 119--128. Google Scholar
Digital Library
- Pujol, J. M., Delgado, J., Sangesa, R., and Flache, A. 2005. The role of clustering on the emergence of efficient social conventions. In Proceedings of the International Joint Conference on Artificial Intelligence. 965--970. Google Scholar
Digital Library
- Rahwan, T. and Jennings, N. 2008a. Coalition structure generation: Dynamic programming meets anytime optimisation. In Proceedings of the 23rd Conference on Artificial Intelligence. 156--161. Google Scholar
Digital Library
- Rahwan, T. and Jennings, N. R. 2008b. An improved dynamic programming algorithm for coalition structure generation. In Proceedings of the 7th International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS’08). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 1417--1420. Google Scholar
Digital Library
- Rahwan, T., Ramchurn, S., Jennings, N., and Giovannucci, A. 2009. An anytime algorithm for optimal coalition structure generation. J. Artif. Intell. Research 34, 521--567. Google Scholar
Digital Library
- Rahwan, T., Michalak, T., and Jennings, N. R. 2012. A hybrid algorithm for coalition structure generation. In Proceedings of the 26th Conference on Artificial Intelligence (AAAI’12). 1443--1449.Google Scholar
- Reka, A. and Barabási, A. 2002. Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47--97.Google Scholar
Cross Ref
- Salazar, N., Rodriguez-Aguilar, J. A., Arcos, J. L., Peleteiro, A., and Burguillo-Rial, J. C. 2011. Emerging cooperation on complex networks. In Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’11). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 669--676. Google Scholar
Digital Library
- Sandholm, T., Larson, K., Andersson, M., Shehory, O., and Tohmé, F. 1999. Coalition structure generation with worst case guarantees. Artif. Intell. 111, 1--2, 209--238. Google Scholar
Digital Library
- Seo, Y.-G., Cho, S.-B., and Yao, X. 1999. Emergence of cooperative coalition in nipd game with localization of interaction and learning. In Proceedings of the Congress on Evolutionary Computation (CEC’99).Google Scholar
- Seo, Y.-G., Cho, S.-B., and Yao, X. 2000. Exploiting coalition in co-evolutionary learning. In Proceedings of the Congress on Evolutionary Computation (CEC’00). 1268--1275Google Scholar
- Service, T. C. and Adams, J. A. 2011. Constant factor approximation algorithms for coalition structure generation. Autonomous Agents Multi-Agent Syst. 23, 1, 1--17. Google Scholar
Digital Library
- Shehory, O. and Kraus, S. 1993. Coalition formation among autonomous agents: Strategies and complexity. In Proceedings of the Conference on Modelling Autonomous Agents in a MultiAgent World. 56--72.Google Scholar
- Shehory, O. and Kraus, S. 1995. Task allocation via coalition formation among autonomous agents. In Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI’95). Morgan Kaufmann Publishers Inc., San Francisco, CA, 655--661. Google Scholar
Digital Library
- Shehory, O. and Kraus, S. 1996. Formation of overlapping coalitions for precedence-ordered task execution among autonomous agents. In Proceedings of the 2nd International Conference on Multiagent Systems (ICMAS’96). 330--337.Google Scholar
- Shehory, O. and Kraus, S. 1998. Methods for task allocation via agent coalition formation. Artif. Intell. 101, 1, 165--200. Google Scholar
Digital Library
- Shehory, O., Sycara, K., and Jha, S. 1998. Multi-agent coordination through coalition formation. In Intelligent Agents IV Agent Theories, Architectures, and Languages, M. Singh, A. Rao, and M. Wooldridge Ed., Lecture Notes in Computer Science, vol. 1365, Springer, 143--154. DOI:10.1007/BFb0026756. Google Scholar
- Shrot, T., Aumann, Y., and Kraus, S. 2010. On agent types in coalition formation problems. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’10). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 757--764. Google Scholar
Digital Library
- Tanimoto, K. 2002. Coalition formation interacted with transitional state of environment. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics.Google Scholar
Cross Ref
- Voice, T., Ramchurn, S. D., and Jennings, N. R. 2012. On coalition formation with sparse synergies. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’12). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 223--230. Google Scholar
Digital Library
- Watts, D. J. and Strogatz, S. 1998. Collective dynamics of ‘small-world’ networks. Nature 393, 6684, 440--442.Google Scholar
- Wooldridge, M. and Dunne, P. E. 2006. On the computational complexity of coalitional resource games. Artif. Intell. 170, 10, 835--871. Google Scholar
Digital Library
- Yee, K. 2003. Ownership and trade from evolutionary games. Int. Rev. Law. Econ. 23, 2, 183--197.Google Scholar
Cross Ref
- Zimmermann, M. G., Eguiluz, V. M., and San Miguel, M. 2004. Coevolution of dynamical states and interactions in dynamic networks. Phys. Rev. E 69, 065102.Google Scholar
Cross Ref
Index Terms
Fostering Cooperation through Dynamic Coalition Formation and Partner Switching
Recommendations
Coalition formation through motivation and trust
AAMAS '03: Proceedings of the second international joint conference on Autonomous agents and multiagent systemsCooperation is the fundamental underpinning of multi-agent systems, allowing agents to interact to achieve their goals. Where agents are self-interested, or potentially unreliable, there must be appropriate mechanisms to cope with the uncertainty that ...
Promoting Cooperation and Fairness in Self-interested Multi-Agent Systems
ICAART 2016: Proceedings of the 8th International Conference on Agents and Artificial IntelligenceThe issue of collaboration amongst agents in a multi-agent system (MAS) represents a challenging research problem. In this paper we focus on a form of cooperation known as coalition formation. The problem we consider is how to facilitate the formation ...
Experiments on robustness and deception in a coalition formation model: Research Articles
Coordination Models and SystemsIn the last few years coalition formation algorithms have been proposed as a possible way of modeling autonomous agent cooperation in multi-agent systems. This work is based on a previously proposed coalition formation model founded on game theory for a ...






Comments