Efficient Multi-Attribute Negotiation with Incomplete Information
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Multi-attribute negotiation is an important mechanism for distributed decision makers to reach agreements in real-world situations. It allows the possibility of reaching “win-win” solutions for both parties, who trade off different attributes in a solution. Existing research on multi-attribute negotiations has mainly focused on the situations when negotiation parties have complete information about each other's preference. This paper presents a model with incomplete information, while considering Pareto-efficiency and computational efficiency. A non-biased mediator, who applies query learning to maintain near Pareto-efficiency without heavy computation, is adopted in the model. In addition, the mediating mechanism proposed in the model overcomes the difficulty of preference elicitation which usually arises in the preliminary step of a multi-attribute negotiation. Our model also reduces the negotiation complexity by decomposing the original n-dimensional negotiation space into a sequence of negotiation base lines. Agents can negotiate upon a base line with rather simple strategies. The experimental results show that near Pareto-efficient agreements can be reached effectively.
Keywordsmulti-attribute negotiation Pareto-efficiency incomplete information win-win mediator
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- Blum, A., J. Jackson, T. Sandholm, and M. Zinkevich (2004). “Preference Elicitation and Query Learning,” Journal of Machine Learning Research 5, 649–667.Google Scholar
- Chen, L. and Pu, P. (2004). “Survey of Preference Elicitation Methods”, EPFL Technical Report IC/2004/67, Switzerland.Google Scholar
- Faratin, P., C. Sierra, and N. R. Jennings (2000). “Using Similarity Criteria to Make Negotiation Trade-Offs,” in the Proceeding of the 4th International Conference on Multi-Agent Systems, Boston, USA. 119–126.Google Scholar
- Fatima, S., M. J. Wooldridge, and N. R. Jennings (2004). “Optimal Negotiation of Multiple issues in incomplete Information Settings,” In the Proceeding of the 3rd International Conference on Autonomous Agents and Multi-Agent Systems, New York, USA., 1080–1087.Google Scholar
- Hudson, B. and T. Sandholm (2004). “Effectiveness of Query Types and Policies for Preference Elicitation in Combinatorial Auctions,” In the Proceeding of the 3rd International Conference on Autonomous Agents and Multi-Agent Systems, New York, USA. , 386–393.Google Scholar
- Lai, G., C. Li, K. Sycara, and J. Giampapa (2004). “Literature review of multi-attribute negotiations”, Technical Report, CMU-RI-TR-04–66, Carnegie Mellon University, Pittsburgh, USA.Google Scholar
- Li, C. and G. Tesauro (2003). “A strategic Decision Model for Multi-attribute Bilateral Negotiation with Alternating Offers,” In the Proceeding of the ACM Conference on Electronic Commerce 2003, 208–209.Google Scholar
- Li, C., J. Giampapa, and K. Sycara (2006). “Bilateral Negotiation Decisions with Uncertain Dynamic Outside Options,” IEEE Transactions on Systems, Man, and Cybernetics, Part C: Special Issue on Game-Theoretic Analysis and Stochastic Simulation of Negotiation Agents 36(1), 31–44.Google Scholar
- Santi, P., V. Conitzer and T. Sandholm (2004). “Towards a Characterization of Polynomial Preference Elicitation with Value Queries in Combinatorial Auctions,” In the Proceedings of the Conference on Computational Learning Theory, Washington DC, USA. , 1–16.Google Scholar
- Sycara, K. (1991). “Problem Restructuring in Negotiation,” Management Science 37, 1248–1268.Google Scholar