Equilibria in Ordinal Games: A Framework based on Possibility Theory.

Equilibria in Ordinal Games: A Framework based on Possibility Theory.

Nahla Ben Amor, Helene Fargier, Régis Sabbadin

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Main track. Pages 105-111. 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.
Keywords:
Agent-based and Multi-agent Systems: Noncooperative Games
Uncertainty in AI: Uncertainty in AI