Skip to Main content Skip to Navigation
Conference papers

Possibilistic games with incomplete information

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.
Complete list of metadatas

Cited literature [9 references]  Display  Hide  Download
Contributor : Open Archive Toulouse Archive Ouverte (oatao) <>
Submitted on : Wednesday, June 24, 2020 - 10:58:04 AM
Last modification on : Friday, August 14, 2020 - 5:52:02 PM


Files produced by the author(s)



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-02879715⟩



Record views


Files downloads