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Communication Dans Un Congrès Année : 2019

Possibilistic games with incomplete information

Résumé

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.
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Dates et versions

hal-02879715 , version 2 (28-11-2019)
hal-02879715 , version 1 (24-06-2020)

Identifiants

Citer

Nahla Ben Amor, Hélène Fargier, Régis Sabbadin, Mariem Trabelsi. Possibilistic games with incomplete information. 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), Aug 2019, Macao, Macau SAR China. pp.1544-1550, ⟨10.24963/ijcai.2019/214⟩. ⟨hal-02879715v1⟩
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