Consensus Policy Based Multi-agent Negotiation
Multiagent negotiation may be understood as a consensus based group decision-making which ideally should seek the agreement of all the participants. However, there exist situations where an unanimous agreement is not possible or simply the rules imposed by the system do not seek such unanimous agreement. In this paper we propose to use a consensus policy based mediation framework (CPMF) to perform multiagent negotiations. This proposal fills a gap in the literature where protocols are in most cases indirectly biased to search for a quorum. The mechanisms proposed to perform the exploration of the negotiation space are derived from the Generalized Pattern Search non-linear optimization technique (GPS). The mediation mechanisms are guided by the aggregation of the agent preferences on the set of alternatives the mediator proposes in each negotiation round. Considerable interest is focused on the implementation of the mediation rules where we allow for a linguistic description of the type of agreements needed. We show empirically that CPMF efficiently manages negotiations following predefined consensus policies and solves situations where unanimous agreements are not viable.
KeywordsOrdered Weight Average Negotiation Protocol Ordered Weight Average Operator Unanimous Agreement Ordered Weight Average
Unable to display preview. Download preview PDF.
- 7.Li, M., Vo, Q.B., Kowalczyk, R.: Searching for fair joint gains in agent-based negotiation. In: Decker, Sichman, Sierra, Castelfranchi (eds.) Proc. of 8th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2009), Budapest, Hungary, May, 10-15, pp. 1049–1056 (2009)Google Scholar
- 9.Lopez-Carmona, M.A., Marsa-Maestre, I., Ibanez, G., Carral, J.A., Velasco, J.R.: Improving trade-offs in automated bilateral negotiations for expressive and inexpressive scenarios. Journal of Intelligent & Fuzzy Systems 21, 165–174 (2010)Google Scholar
- 10.Lopez-Carmona, M.A., Marsa-Maestre, I., Klein, M., Ito, T.: Addressing stability issues in mediated complex contract negotiations for constraint-based, non-monotonic utility spaces. Journal of Autonomous Agents and Multiagent Systems, 1–51 (2010)Google Scholar
- 11.Marsa-Maestre, I., Lopez-Carmona, M.A., Velasco, J.R., Ito, T., Klein, M., Fujita, K.: Balancing utility and deal probability for auction-based negotiations in highly nonlinear utility spaces. In: 21st International Joint Conference on Artificial Intelligence (IJCAI 2009), Pasadena, California, USA, pp. 214–219 (July 2009)Google Scholar
- 14.Yager, R., Kacprzyk, J.: The Ordered Weighted Averaging Operators: Theory and Applications. Kluwer (1997)Google Scholar