Abstract
This paper focuses on enabling the use of negotiation for complex system optimisation, whose main challenge nowadays is scalability. Although multi-agent automated negotiation has been studied for decades, it is still a challenge to handle in a scalable and efficient manner negotiation problems involving many issues with complex interdependencies. This is a clear obstacle for the use of automated negotiation in complex networks. This paper proposes a novel perspective on the negotiation process as a competitive belief propagation process, where the whole negotiation is modelled as a factor graph and distributed belief propagation techniques (BP) are used to yield a solution. We show that the model adequately suits both simple and complex negotiation settings in the literature, and we validate its efficiency and scalability in a challenging, network structured, channel negotiation setting.
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References
An, B., Lesser, V., Sim, K.M.: Strategic agents for multi-resource negotiation. Auton. Agent. Multi-Agent Syst. 23(1), 114–153 (2011)
Baarslag, T., Dirkzwager, A., Hindriks, K.V., Jonker, C.M.: The significance of bidding, accepting and opponent modeling in automated negotiation. In: Proceedings of the Twenty-First European Conference on Artificial Intelligence, pp. 27–32. IOS Press (2014)
De La Hoz, E., Gimenez-Guzman, J.M., Marsa-Maestre, I., Orden, D.: A realistic scenario for complex automated nonlinear negotiation: Wi-Fi channel assignment. In: Proceedings of the the Ninth International Workshop on Agent-based Complex Automated Negotiations (ACAN2016), Singapore (2016)
De La Hoz, E., Marsa-Maestre, I., Gimenez-Guzman, J.M., Orden, D., Klein, M.: Multi-agent nonlinear negotiation for Wi-Fi channel assignment. In: Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017, International Foundation for Autonomous Agents and Multiagent Systems, Sao Paulo, Brazil (2017)
Demers, A., Greene, D., Hauser, C., Irish, W., Larson, J., Shenker, S., Sturgis, H., Swinehart, D., Terry, D.: Epidemic algorithms for replicated database maintenance. In: Proceedings of the Sixth Annual ACM Symposium on Principles of Distributed Computing, PODC 1987, New York, NY, USA, pp. 1–12 (1987)
Faratin, P., Sierra, C., Jennings, N.R.: Using similarity criteria to make issue trade-offs in automated negotiations. Artif. Intell. 142(2), 205–237 (2002)
Fatima, S., Kraus, S., Wooldridge, M.: Principles of Automated Negotiation. Cambridge University Press, Cambridge (2014)
Fujita, K., Ito, T., Klein, M.: A secure and fair protocol that addresses weaknesses of the nash bargaining solution in nonlinear negotiation. Group Decis. Negot. 21(1), 29–47 (2012)
Gamarnik, D., Shah, D., Wei, Y.: Belief propagation for min-cost network flow: convergence and correctness. Oper. Res. 60(2), 410–428 (2012)
Grubshtein, A., Meisels, A.: A distributed cooperative approach for optimizing a family of network games. In: Brazier, F.M.T., Nieuwenhuis, K., Pavlin, G., Warnier, M., Badica, C. (eds.) Intelligent Distributed Computing V: Proceedings of the 5th International Symposium on Intelligent Distributed Computing - IDC 2011, pp. 49–62. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-24013-3_6
Hadfi, R., Ito, T.: Complex multi-issue negotiation using utility hyper-graphs. JACIII 19(4), 514–522 (2015)
Hattori, H., Klein, M., Ito, T.: Using iterative narrowing to enable multi-party negotiations with multiple interdependent issues. In: Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2007, pp. 247:1–247:3. ACM, New York (2007)
de la Hoz, E., Gimenez-Guzman, J.M., Marsa-Maestre, I., Orden, D.: Automated negotiation for resource assignment in wireless surveillance sensor networks. Sensors 15(11), 29547–29568 (2015)
Kinney, R., Crucitti, P., Albert, R., Latora, V.: Modeling cascading failures in the North American power grid. Eur. Phys. J. B-Condens. Matter Complex Syst. 46(1), 101–107 (2005)
Klein, M., Faratin, P., Sayama, H., Bar-Yam, Y.: Negotiating complex contracts. Group Decis. Negot. 12(2), 111–125 (2003)
Lang, F., Fink, A.: Learning from the metaheuristics: protocols for automated negotiations. Group Decis. Negot. 24(2), 299–332 (2015)
Lopez-Carmona, M.A., Marsa-Maestre, I., Ibañez, G., Carral, J.A., Velasco, J.R.: Improving trade-offs in automated bilateral negotiations for expressive and inexpressive scenarios. J. Intell. Fuzzy Syst. 21(3), 165–174 (2010)
Marsa-Maestre, I., Lopez-Carmona, M.A., Velasco, J.R., de la Hoz, E.: Effective bidding and deal identification for negotiations in highly nonlinear scenarios. In: Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2, AAMAS 2009, International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, pp. 1057–1064 (2009)
Orden, D., Marsá-Maestre, I., Giménez-Guzmán, J.M., de la Hoz, E.: Spectrum graph coloring and applications to WiFi channel assignment. CoRR abs/1602.05038 (2016)
Osorio, C., Bierlaire, M.: Mitigating network congestion: analytical models, optimization methods and their applications. In: 90th Annual Meeting, No. EPFL-TALK-196049 (2011)
Pelikan, M., Sastry, K., Goldberg, D.E.: Multiobjective estimation of distribution algorithms. In: Pelikan, M., Sastry, K., CantúPaz, E. (eds.) Scalable Optimization via Probabilistic Modeling, pp. 223–248. Springer, Heidelberg (2006). https://doi.org/10.1007/978-3-540-34954-9_10
Schaller, B.: New York City’s congestion pricing experience and implications for road pricing acceptance in the United States. Transp. Pol. 17(4), 266–273 (2010)
Tuza, Z., Gutin, G., Plurnmer, M., Tucker, A., Burke, E., Werra, D., Kingston, J.: Colorings and related topics. Handbook of Graph Theory. Discrete Mathematics and Its Applications, pp. 340–483. CRC Press, Boca Raton (2003)
Vytelingum, P., Ramchurn, S.D., Voice, T.D., Rogers, A., Jennings, N.R.: Trading agents for the smart electricity grid. In: Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: Volume 1, International Foundation for Autonomous Agents and Multiagent Systems, pp. 897–904 (2010)
Zheng, L., Mengshoel, O.: Optimizing parallel belief propagation in junction treesusing regression. In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, ACM, Chicago, Illinois, USA, pp. 757–765 (2013)
Acknowledgments
This work has been supported by the Spanish Ministry of Economy and Competitiveness grants TIN2016-80622-P, TIN2014-61627-EXP, MTM2014-54207 and TEC2013-45183-R, and by the University of Alcala through CCG2016/EXP-048.
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Marsa-Maestre, I., Gimenez-Guzman, J.M., de la Hoz, E., Orden, D. (2017). Competitive Belief Propagation to Efficiently Solve Complex Multi-agent Negotiations with Network Structure. In: Sukthankar, G., Rodriguez-Aguilar, J. (eds) Autonomous Agents and Multiagent Systems. AAMAS 2017. Lecture Notes in Computer Science(), vol 10643. Springer, Cham. https://doi.org/10.1007/978-3-319-71679-4_1
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DOI: https://doi.org/10.1007/978-3-319-71679-4_1
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