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This paper introduces an axiomatic model for bargaining analysis. We describe a bargaining situation in propositional logic and represent bargainers' preferences in total pre-orders. Based on the concept of minimal simultaneous concessions, we propose a solution to n-person bargaining problems and prove that the solution is uniquely characterized by five logical axioms: Consistency, Comprehensiveness, Collective rationality, Disagreement, and Contraction independence. This framework provides a naive solution to multi-person, multi-issue bargaining problems in discrete domains. Although the solution is purely qualitative, it can also be applied to continuous bargaining problems through a procedure of discretization, in which case the solution coincides with the Kalai-Smorodinsky solution.

Abstract. As a contribution to the challenge of building game-playing AI systems, we develop and analyse a formal language for representing and reasoning about strategies. Our logical language builds on the existing general Game Description Language (GDL) and extends it by a standard modality for linear time along with two dual connectives to express preferences when combining strategies. The semantics of the language is provided by a standard state-transition model. As such, problems that require reasoning about games can be solved by the standard methods for reasoning about actions and change. We also endow the language with a specific semantics by which strategy formulas are understood as move recommendations for a player. To illustrate how our formalism supports automated reasoning about strategies, we demonstrate two example methods of implementation: first, we formalise the semantic interpretation of our language in conjunction with game rules and strategy rules in the Situation Calculus; second, we show how the reasoning problem can be solved with Answer Set Programming.