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Possibilistic games with incomplete information

Ben Amor, Nahla and Fargier, Hélène and Sabbadin, Régis and Trabelsi, Mariem Possibilistic games with incomplete information. (2019) In: 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), 10 August 2019 - 16 August 2019 (Macao, Macao).

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Official URL: https://doi.org/10.24963/ijcai.2019/214

Abstract

Bayesian games offer a suitable framework for games where the utility degrees are additive in essence. This approach does nevertheless not apply to ordinal games, where the utility degrees do not capture more than a ranking, nor to situations of decision under qualitative uncertainty. This paper proposes a representation framework for ordinal games under possibilistic incomplete information (π-games) and extends the fundamental notion of Nash equilibrium (NE) to this framework. We show that deciding whether a NE exists is a difficult problem (NP-hard) and propose a Mixed Integer Linear Programming (MILP) encoding. Experiments on variants of the GAMUT problems confirm the feasibility of this approach.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-02879715
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
French research institutions > Institut National de la Recherche Agronomique - INRA (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Université de Tunis (TUNISIA)
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Deposited On:19 Jun 2020 11:11

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