Approximating constraint-based utility spaces using generalized gaussian mixture models

Rafik Hadfi, Takayuki Ito

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Complex negotiations are characterized by a particular type of utility spaces that is usually non-linear and non-monotonic. An example of such utility spaces are constraint-based utility spaces. The multitude of constraints’ shapes that could potentially be used by the negotiating agents makes any opponent modeling attempt more challenging. The same problem persists even when the agent is exploring her own utility space as to find her optimal contracts. Seeking a unified form for constraint-based utility representation might shed some light on how to tackle these problems.

In this paper, we propose to find an approximation for constraint-based preferences, used mainly in complex negotiation with non-linear utility spaces. The proposed approximation yields a compact form that unifies a whole family of constraints (Cubic, Bell, Conic, etc.). Results show that the new canonical form can in fact be an alternative representation for all known constraint-based utility functions. Additionally, it leads us to a potential parametric model that could be used for opponent modeling in complex non-linear negotiations.

Original languageEnglish
Title of host publicationPRIMA 2014
Subtitle of host publicationPrinciples and Practice of Multi-Agent Systems - 17th International Conference, Proceedings
EditorsHoa Khanh Dam, Jeremy Pitt, Yang Xu, Guido Governatori, Takayuki Ito
Place of PublicationSwitzerland
PublisherSpringer
Pages133-140
Number of pages8
ISBN (Electronic)9783319131917
ISBN (Print)9783319131900
Publication statusPublished - 1 Jan 2014
Externally publishedYes
EventInternational Conference on Principles of Practice in Multi-Agent Systems 2014 - Gold Coast, Australia
Duration: 1 Dec 20145 Dec 2014
Conference number: 17th
https://link.springer.com/book/10.1007/978-3-319-13191-7 (Proceedings)

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8861
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Principles of Practice in Multi-Agent Systems 2014
Abbreviated titlePRIMA 2014
CountryAustralia
CityGold Coast
Period1/12/145/12/14
Internet address

Cite this

Hadfi, R., & Ito, T. (2014). Approximating constraint-based utility spaces using generalized gaussian mixture models. In H. K. Dam, J. Pitt, Y. Xu, G. Governatori, & T. Ito (Eds.), PRIMA 2014: Principles and Practice of Multi-Agent Systems - 17th International Conference, Proceedings (pp. 133-140). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8861). Switzerland: Springer.
Hadfi, Rafik ; Ito, Takayuki. / Approximating constraint-based utility spaces using generalized gaussian mixture models. PRIMA 2014: Principles and Practice of Multi-Agent Systems - 17th International Conference, Proceedings. editor / Hoa Khanh Dam ; Jeremy Pitt ; Yang Xu ; Guido Governatori ; Takayuki Ito. Switzerland : Springer, 2014. pp. 133-140 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Hadfi, R & Ito, T 2014, Approximating constraint-based utility spaces using generalized gaussian mixture models. in HK Dam, J Pitt, Y Xu, G Governatori & T Ito (eds), PRIMA 2014: Principles and Practice of Multi-Agent Systems - 17th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8861, Springer, Switzerland, pp. 133-140, International Conference on Principles of Practice in Multi-Agent Systems 2014, Gold Coast, Australia, 1/12/14.

Approximating constraint-based utility spaces using generalized gaussian mixture models. / Hadfi, Rafik; Ito, Takayuki.

PRIMA 2014: Principles and Practice of Multi-Agent Systems - 17th International Conference, Proceedings. ed. / Hoa Khanh Dam; Jeremy Pitt; Yang Xu; Guido Governatori; Takayuki Ito. Switzerland : Springer, 2014. p. 133-140 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8861).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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Hadfi R, Ito T. Approximating constraint-based utility spaces using generalized gaussian mixture models. In Dam HK, Pitt J, Xu Y, Governatori G, Ito T, editors, PRIMA 2014: Principles and Practice of Multi-Agent Systems - 17th International Conference, Proceedings. Switzerland: Springer. 2014. p. 133-140. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).