Approximating constraint-based utility spaces using generalized gaussian mixture models

Rafik Hadfi; Takayuki Ito

Approximating constraint-based utility spaces using generalized gaussian mixture models

Rafik Hadfi, Takayuki Ito

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-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 language	English
Title of host publication	PRIMA 2014
Subtitle of host publication	Principles and Practice of Multi-Agent Systems - 17th International Conference, Proceedings
Editors	Hoa Khanh Dam, Jeremy Pitt, Yang Xu, Guido Governatori, Takayuki Ito
Place of Publication	Switzerland
Publisher	Springer
Pages	133-140
Number of pages	8
ISBN (Electronic)	9783319131917
ISBN (Print)	9783319131900
Publication status	Published - 1 Jan 2014
Externally published	Yes
Event	International Conference on Principles of Practice in Multi-Agent Systems 2014 - Gold Coast, Australia Duration: 1 Dec 2014 → 5 Dec 2014 Conference number: 17th https://link.springer.com/book/10.1007/978-3-319-13191-7 (Proceedings)

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8861
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Principles of Practice in Multi-Agent Systems 2014
Abbreviated title	PRIMA 2014
Country	Australia
City	Gold Coast
Period	1/12/14 → 5/12/14
Internet address	https://link.springer.com/book/10.1007/978-3-319-13191-7 (Proceedings)

Access to Document

Link to publication in Scopus

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). 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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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{\textquoteright} 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.",

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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 proceeding › Conference Paper › Research › peer-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)).