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Negotiating with bounded rational agents in environments with incomplete information using an automated agent. (English) Zbl 1182.68311
Summary: Many tasks in day-to-day life involve interactions among several people. Many of these interactions involve negotiating over a desired outcome. Negotiation in and of itself is not an easy task, and it becomes more complex under conditions of incomplete information. For example, the parties do not know in advance the exact tradeoff of their counterparts between different outcomes. Furthermore information regarding the preferences of counterparts might only be elicited during the negotiation process itself. In this paper we propose a model for an automated negotiation agent capable of negotiating with bounded rational agents under conditions of incomplete information. We test this agent against people in two distinct domains, in order to verify that its model is generic, and thus can be adapted to any domain as long as the negotiators’ preferences can be expressed in additive utilities. Our results indicate that the automated agent reaches more agreements and plays more effectively than its human counterparts. Moreover, in most of the cases, the automated agent achieves significantly better agreements, in terms of individual utility, than the human counterparts playing the same role.

MSC:
68T42 Agent technology and artificial intelligence
91A26 Rationality and learning in game theory
91B26 Auctions, bargaining, bidding and selling, and other market models
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[1] Brafman, R.I.; Tennenholtz, M., An axiomatic treatment of three qualitative decision criteria, Journal of the ACM, 47, 3, 452-482, (2000) · Zbl 1094.91503
[2] Brown, S.R.; Melamed, L.E., Experimental design and analysis, (1990), Sage Publications, Inc. CA
[3] Capra, C.M.; Goeree, J.K.; Gomez, R.; Holt, C.A., Anomalous behavior in a Traveler’s dilemma?, American economic review, 89, 3, 678-690, (1999), (June 1999)
[4] Dubois, D.; Prade, H.; Sabbadin, R., Decision-theoretic foundations of qualitative possibility theory, European journal of operational research, 128, 459-478, (2001) · Zbl 0982.90028
[5] Faratin, P.; Sierra, C.; Jennings, N.R., Using similarity criteria to make issue trade-offs in automated negotiations, Aij, 142, 2, 205-237, (2002)
[6] Fatima, S.; Wooldridge, M., An agenda based framework for multi-issue negotiation, Aij, 152, 1-45, (2004) · Zbl 1082.91510
[7] Fatima, S.; Wooldridge, M.; Jennings, N.R., Bargaining with incomplete information, Amai, 44, 3, 207-232, (2005) · Zbl 1123.91315
[8] Gibbons, J.D.; Chakraborty, S., Nonparametric statistical inference, (1992), Marcel Dekker New York
[9] Hoppman, P.T., The negotiation process and the resolution of international conflicts, (1996), University of South Carolina Press Columbia, SC
[10] Keeney, R.; Raiffa, H., Decisions with multiple objective: preferences and value tradeoffs, (1976), John Wiley & Sons New York
[11] Kraus, S.; Hoz-Weiss, P.; Wilkenfeld, J.; Andersen, D.R.; Pate, A., Resolving crises through automated bilateral negotiations, Artificial intelligence, 172, 1, 1-18, (2008) · Zbl 1182.91047
[12] Leonard, T.; Hsu, J.S.J., Bayesian methods—an analysis for statisticians and interdisciplinary researchers, (1999), Cambridge University Press Cambridge · Zbl 0930.62023
[13] R.J. Lin, S.T. Chou, Bilateral multi-issue negotiations in a dynamic environment, in: Proc. of the AAMAS Workshop on Agent Mediated Electronic Commerce (AMEC V), Melbourne, Australia, 2003
[14] R. Lin, S. Kraus, J. Wilkenfeld, J. Barry, An automated agent for bilateral negotiation with bounded rational agents with incomplete information, in: Proc. of ECAI-06, 2006, pp. 270-274
[15] Luce, R.D., Individual choice behavior: A theoretical analysis, (1959), John Wiley & Sons New York · Zbl 0093.31708
[16] Luce, R.D., The choice axiom after twenty years, Journal of mathematical psychology, 15, 215-233, (1977) · Zbl 0357.92033
[17] Luce, R.D.; Raiffa, H., Games and decisions—introduction and critical survey, (1957), John Wiley & Sons New York · Zbl 0084.15704
[18] Nash, J.F., The bargaining problem, Econ., 18, 155-162, (1950) · Zbl 1202.91122
[19] Oprea, M., An adaptive negotiation model for agent-based electronic commerce, Studies in informatics and control, 11, 3, 271-279, (2002)
[20] Osborne, M.J.; Rubinstein, A., A course in game theory, (1994), MIT Press Cambridge, MA · Zbl 1194.91003
[21] Rasmusen, E., Games and information: an introduction to game theory, (February 2001), Blackwell Publishers
[22] Siegel, S., Non-parametric statistics for the behavioral sciences, (1956), McGraw-Hill New York
[23] Stitt feld handy group online negotiation course, (2007)
[24] M. Tennenholtz, On stable social laws and qualitative equilibrium for risk-averse agents, in: KR, 1996, pp. 553-561
[25] Wilkenfeld, J.; Young, K.; Quinn, D.; Asal, V., Mediating international crises, (2005), Routledge London
[26] Zeng, D.; Sycara, K., Bayesian learning in negotiation, (), 99-104
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