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Effective bidding and deal identification for negotiations in highly nonlinear scenarios

Authors:

Ivan Marsa-Maestre,

Miguel A. Lopez-Carmona,

Juan R. Velasco,

Enrique de la HozAuthors Info & Claims

AAMAS '09: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2

Pages 1057 - 1064

Published: 10 May 2009 Publication History

Abstract

Most real-world negotiation scenarios involve multiple, inter-dependent issues. These scenarios are specially challenging because the agents' utility functions are nonlinear, which makes traditional negotiation mechanisms not applicable. Even mechanisms designed and proven useful for nonlinear utility spaces may fail if the utility space is highly nonlinear. For example, simulated annealing has been used successfully in bidding based negotiations with constraint-based utility spaces to identify high utility regions in the contract space, and to send these regions as bids to a mediator. In this paper, we will show that the performance of this approach decreases drastically in highly nonlinear scenarios, and propose alternative mechanisms for the bidding process which take advantage of the constraint-based preference model. Also, we propose a probabilistic search method for the mediator to improve the scalability of the deal identification process, and an iterative, expressive negotiation protocol to give feed-back to the agents in case no deals have been found with the initial bids. The experiments show that the proposed mechanisms yield better results than the previous approach in highly nonlinear negotiation scenarios.

References

[1]

M. Bayati, D. Shah, and M. Sharma. Max-product for maximum weight matching: Convergence, correctness, and lp duality. IEEE Transactions on Information Theory, 54(3):1241--1251, 2008.

Digital Library

[2]

Y. Chevaleyre, U. Endriss, S. Estivie, and N. Maudet. Multiagent resource allocation with k-additive utility functions. In Proceedings of the DIMACS-LAMSADE Workshop on Computer Science and Decision Theory, pages 83--100, 2004.

[3]

P. Faratin, C. Sierra, and N. Jennings. Using similarity criteria to make negotiation trade-offs. In Proceedings of the 4th International Conference on Multi-Agent Systems, pages 119--126, 2000.

Digital Library

[4]

V. U. Gnanasekaran. Improved opportunity cost algorithm for carrier selection in combinatorial auctions. Master's thesis, Louisiana State University, 2004.

[5]

K. Hindriks, C. M. Jonker, and D. Tykhonov. Eliminating interdependencies between issues for multi-issue negotiation. In Cooperative Information Agents X, volume 4149 of Lecture Notes in Computer Science, pages 301--316, 2006.

Digital Library

[6]

G. Hohner, J. Rich, E. Ng, G. Reid, A. J. Davenport, J. R. Kalagnanam, H. S. Lee, and C. An. Combinatorial and quantity-discount procurement auctions benefit mars, incorporated and its suppliers. Interfaces, 33(1):23--35, 2003.

[7]

T. Ito, M. Klein, and H. Hattori. A multi-issue negotiation protocol among agents with nonlinear utility functions. Multiagent and Grid Systems, 4(1):67--83.

Digital Library

[8]

T. Ito, M. Klein, and H. Hattori. Multi-issue negotiation protocol for agents: Exploring nonlinear utility spaces. In Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI07), pages 1347--1352, 2007.

Digital Library

[9]

M. Klein, P. Faratin, H. Sayama, and Y. Bar-Yam. Protocols for negotiating complex contracts. IEEE Intelligent Systems, 18(6):32--38, 2003.

Digital Library

[10]

V. Kumar and L. Kanal. A general branch-and-bound formulations for understanding and synthesizing and/or tree search procedures. Artificial Intelligence, 21:179--198, 1983.

Digital Library

[11]

M. A. Lopez-Carmona and J. R. Velasco. An expressive approach to fuzzy constraint based agent purchase negotiation. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS06), 2006.

Digital Library

[12]

M. A. Lopez-Carmona, J. R. Velasco, and I. Marsa-Maestre. The agents' attitudes in fuzzy constraint based automated purchase negotiations. In Multi-Agent Systems and Applications V, volume 4696/2007 of Lecture Notes in Artificial Intelligence, pages 246--255. Springer, 2007.

Digital Library

[13]

I. Marsa-Maestre, M. A. Lopez-Carmona, and J. R. Velasco. Improving trade-offs in bilateral negotiations under complete and incomplete information settings. In Proceedings of the Pacific Rim International Conference on Multi-Agents, volume 5357 of Lecture Notes in Artificial Intelligence, pages 275--286, 2008.

Digital Library

[14]

B. L. Miller and D. E. Goldberg. Genetic algorithms, tournament selection, and the effects of noise. Complex Systems, 9(3):193--212, 1995.

[15]

N. Nisan. Bidding languages for combinatorial auctions, chapter 9. MIT Press, 2006.

[16]

A. Schrijver. Theory of Linear and Integer Programming 1998. John Wiley and Sons, 1998.

Digital Library

Cited By

de Jonge DZhang DLarson KWinikoff MDas SDurfee E(2017)Automated Negotiations for General Game PlayingProceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems10.5555/3091125.3091183(371-379)Online publication date: 8-May-2017
https://dl.acm.org/doi/10.5555/3091125.3091183
Jonge DSierra C(2017)D-BraneApplied Intelligence10.1007/s10489-017-0919-y47:1(158-177)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.1007/s10489-017-0919-y
Fujita KIto TKlein M(2014)AN APPROACH TO SCALABLE MULTI-ISSUE NEGOTIATIONComputational Intelligence10.1111/j.1467-8640.2012.00462.x30:1(30-47)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.1111/j.1467-8640.2012.00462.x
Show More Cited By

Index Terms

Effective bidding and deal identification for negotiations in highly nonlinear scenarios
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Cooperation and coordination
      2. Multi-agent systems
    2. Search methodologies
      1. Heuristic function construction

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Information & Contributors

Information

Published In

cover image Guide Proceedings

AAMAS '09: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2

May 2009

730 pages

ISBN:9780981738178

General Chairs:
Carles Sierra
Artificial Intelligence Research Institute of the Spanish Research Council (Spain)
,
Cristiano Castelfranchi
ISTC-CNR (Italy)
,
Program Chairs:
Keith S. Decker
University of Delaware
,
Jaime Simão Sichman
Politecnic School, University of São Paulo (Brazil)

Sponsors

Drexel University
Wiley-Blackwell
Microsoft Research: Microsoft Research
Whitestein Technologies
European Office of Aerospace Research and Development, Air Force Office of Scientific Research, United States Air Force Research Laboratory
The Foundation for Intelligent Physical Agents

Publisher

International Foundation for Autonomous Agents and Multiagent Systems

Richland, SC

Publication History

Published: 10 May 2009

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Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Citations

Cited By

de Jonge DZhang DLarson KWinikoff MDas SDurfee E(2017)Automated Negotiations for General Game PlayingProceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems10.5555/3091125.3091183(371-379)Online publication date: 8-May-2017
https://dl.acm.org/doi/10.5555/3091125.3091183
Jonge DSierra C(2017)D-BraneApplied Intelligence10.1007/s10489-017-0919-y47:1(158-177)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.1007/s10489-017-0919-y
Fujita KIto TKlein M(2014)AN APPROACH TO SCALABLE MULTI-ISSUE NEGOTIATIONComputational Intelligence10.1111/j.1467-8640.2012.00462.x30:1(30-47)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.1111/j.1467-8640.2012.00462.x
Adabi SMovaghar AMasoud Rahmani ABeigy HDastmalchy-Tabrizi H(2014)A new fuzzy negotiation protocol for grid resource allocationJournal of Network and Computer Applications10.1016/j.jnca.2012.12.03037(89-126)Online publication date: 1-Jan-2014
https://dl.acm.org/doi/10.1016/j.jnca.2012.12.030
SáNchez-Anguix VValero SJuliáN VBotti VGarcíA-Fornes A(2013)Evolutionary-aided negotiation model for bilateral bargaining in Ambient Intelligence domains with complex utility functionsInformation Sciences: an International Journal10.1016/j.ins.2010.11.018222(25-46)Online publication date: 1-Feb-2013
https://dl.acm.org/doi/10.1016/j.ins.2010.11.018
de Jonge DSierra C(2012)Branch and Bound for negotiations in large agreement spacesProceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 310.5555/2343896.2344035(1415-1416)Online publication date: 4-Jun-2012
https://dl.acm.org/doi/10.5555/2343896.2344035
Zhang XKlein M(2012)Hierarchical Negotiation Model for Complex Problems with Large-Number of Interdependent IssuesProceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 0210.1109/WI-IAT.2012.185(126-133)Online publication date: 4-Dec-2012
https://dl.acm.org/doi/10.1109/WI-IAT.2012.185
Marsa-Maestre ILopez-Carmona MVelasco Jde la Hoz ELuck MSen S(2010)Avoiding the prisoner's dilemma in auction-based negotiations for highly rugged utility spacesProceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 110.5555/1838206.1838266(425-432)Online publication date: 10-May-2010
https://dl.acm.org/doi/10.5555/1838206.1838266
Fujita KIto TKlein M(2010)Secure and efficient protocols for multiple interdependent issues negotiationJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.5555/1735086.173508921:3(175-185)Online publication date: 1-Aug-2010
https://dl.acm.org/doi/10.5555/1735086.1735089
Lopez-Carmona MMarsa-Maestre IHoz EVelasco J(2009)NegoExplorerProceedings of the 12th International Conference on Principles of Practice in Multi-Agent Systems10.1007/978-3-642-11161-7_18(261-275)Online publication date: 15-Dec-2009
https://dl.acm.org/doi/10.1007/978-3-642-11161-7_18

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