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Equilibria in Ordinal Games:A Framework based on Possibility Theory

Ben Amor, Nahla and Fargier, Hélène and Sabbadin, Régis Equilibria in Ordinal Games:A Framework based on Possibility Theory. (2017) In: 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), 19 August 2017 - 25 August 2017 (Melbourne, Australia).

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Official URL: https://doi.org/10.24963/ijcai.2017/16


The present paper proposes the first definition of mixed equilibrium for ordinal games. This definition naturally extends possibilistic (single agent) decision theory. This allows us to provide a unifying view of single and multi-agent qualitative decision theory. Our first contribution is to show that ordinal games always admit a possibilistic mixed equilibrium, which can be seen as a qualitative counterpart to mixed (probabilistic) equilibrium.Then, we show that a possibilistic mixed equilibrium can be computed in polynomial time (wrt the size of the game), which contrasts with pure Nash or mixed probabilistic equilibrium computation in cardinal game theory.The definition we propose is thus operational in two ways: (i) it tackles the case when no pure Nash equilibrium exists in an ordinal game; and (ii) it allows an efficient computation of a mixed equilibrium.

Item Type:Conference or Workshop Item (Paper)
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:
Agence nationale de la recherche - ANR (FRANCE)
Deposited On:06 Mar 2020 15:44

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