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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(Document in English)
PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 365kB |
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) |
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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) |
Laboratory name: | |
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Deposited On: | 19 Jun 2020 11:11 |
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