Abstract
In this work we consider a group decision making problem where a number of agents try to reach an agreement through a mediated automated negotiation process. Each participating agent provides her preferences over the sets of contracts proposed by the mediator in successive mediation steps. Then, individual preferences are aggregated to obtain a group preference function for choosing the most preferred contract. The negotiation process involves a set of mediation rules to explore efficiently the alternatives space, which is derived from the Generalized Pattern Search non-linear optimization algorithm. A particularly notable feature of our approach is the inclusion of mechanisms rewarding the agents for being open to alternatives other than simply their most preferred. The proposed negotiation framework avoids selfish behavior and improves social welfare. We show empirically that our approach obtains satisfactory results under smooth non-linear utility spaces.
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
References
T. Calvo, G. Mayor, R. Mesiar, Aggregation Operators: New Trends and Applications, vol. 97 (Springer, New York, 2002)
E. de la Hoz, M.A. López-Carmona, M. Klein, I. Marsá-Maestre, Consensus policy based multi-agent negotiation, in Proceedings of the Agents in Principle, Agents in Practice - 14th International Conference, PRIMA 2011, Wollongong, Australia, 16–18 November 2011, pp. 159–173
E. de la Hoz, M.A. López-Carmona, M. Klein, I. Marsá-Maestre, Hierarchical clustering and linguistic mediation rules for multiagent negotiation, in International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2012, Valencia, Spain, 4–8 June 2012 (3 Volumes), pp. 1259–1260 http://dl.acm.org/citation.cfm?id=2343952
E. de la Hoz, M.A. López-Carmona, M. Klein, I. Marsá-Maestre, Consortium formation using a consensus policy based negotiation framework, Complex Automated Negotiations: Theories, Models, and Software Competitions (Springer, Berlin, 2013), pp. 3–22
H. Ehtamo, R.P. Hamalainen, P. Heiskanen, J. Teich, M. Verkama, S. Zionts, Generating pareto solutions in a two-party setting: constraint proposal methods. Manag. Sci. 45(12), 1697–1709 (1999)
P. Heiskanen, H. Ehtamo, R.P. Hamalainen, Constraint proposal method for computing Pareto solutions in multi-party negotiations. Eur. J. Oper. Res. 133(1), 44–61 (2001)
T. Ito, M. Klein, H. Hattori, A multi-issue negotiation protocol among agents with nonlinear utility functions. J. Multiagent Grid Syst. 4(1), 67–83 (2008)
M. Klein, P. Faratin, H. Sayama, Y. Bar-Yam, Protocols for negotiating complex contracts. IEEE Intell. Syst. 18(6), 32–38 (2003)
G. Lai, K. Sycara, A generic framework for automated multi-attribute negotiation. Group Decis. Negot. 18, 169–187 (2009)
F. Lang, A. Fink, Learning from the metaheuristics: protocols for automated negotiations. Group Decis. Negot. 24(2), 299–332 (2015). doi:10.1007/s10726-014-9390-x
R.M. Lewis, V. Torczon, M.W. Trosset, Direct search methods: then and now. J. Comput. Appl. Math. 124, 191–207 (2000)
M. Li, Q.B. Vo, R. Kowalczyk, Searching for fair joint gains in agent-based negotiation, in Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), ed. By S. Decker, C. Sierra, Budapest, Hungary (2009), pp. 1049–1056
M.A. Lopez-Carmona, I. Marsa-Maestre, E. de la Hoz, J.R. Velasco, A region-based multi-issue negotiation protocol for non-monotonic utility spaces, in Computational Intelligence (In press), pp. 1–48 (2011), doi:10.1007/s10458-010-9159-9
M.A. Lopez-Carmona, I. Marsa-Maestre, M. Klein, T. Ito, Addressing stability issues in mediated complex contract negotiations for constraint-based, non-monotonic utility spaces. J. Auton. Agents Multiagent Syst. 1–51 (2010) (Published online)
I. Marsa-Maestre, M.A. Lopez-Carmona, J.R. Velasco, T. Ito, M. Klein, K. Fujita, 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 (2009), pp. 214–219
D. Pelta, R. Yager, Analyzing the robustness of decision strategies in multiagent decision making. Group Decis. Negot. 23(6), 1403–1416 (2014). doi:10.1007/s10726-013-9376-0
D.A. Pelta, R.R. Yager, Decision strategies in mediated multiagent negotiations: an optimization approach. IEEE Trans. Syst. Man Cybern. Part A 40(3), 635–640 (2010). doi:10.1109/TSMCA.2009.2036932
Q.B. Vo, L. Padgham, L. Cavedon, Negotiating flexible agreements by combining distributive and integrative negotiation. Intell. Decis. Technol. 1(1–2), 33–47 (2007)
R. Yager, Multi-agent negotiation using linguistically expressed mediation rules. Group Decis. Negot. 16(1), 1–23 (2007)
R. Yager, J. Kacprzyk, The Ordered Weighted Averaging Operators: Theory and Applications (Kluwer, Boston, 1997)
Acknowledgements
This work has been supported by the Spanish Ministry of Economy and Competitiveness grant: TEC2013-45183-R CIVTRAff.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Lopez-Carmona, M.A., Marsa-Maestre, I., de la Hoz, E. (2017). A Cooperative Framework for Mediated Group Decision Making. In: Fujita, K., et al. Modern Approaches to Agent-based Complex Automated Negotiation. Studies in Computational Intelligence, vol 674. Springer, Cham. https://doi.org/10.1007/978-3-319-51563-2_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-51563-2_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-51561-8
Online ISBN: 978-3-319-51563-2
eBook Packages: EngineeringEngineering (R0)