Solving possibilistic games with incomplete information

Bayesian games offer a suitable framework for where the utility degrees are additive in essence. This approach does nevertheless not apply to ordinal games, do capture more than ranking, nor situations of decision under qualitative uncertainty. The present paper proposes representation possibilistic incomplete information and extends fundamental notions pure mixed Nash equilibrium this framework. We show that deciding whether exists is difficult task (NP-hard) propose Mixed Integer Linear Programming (MILP) encoding problem; as problem computing equilibrium, we it can be solved polynomial time. An experimental study based on GAMUT game generator confirms feasibility approach.