The need for computationally efficient decision making techniques together with the desire to simplify the processes of knowledge acquisition and agent specification have led various researchers in artificial intelligence to examine qualitative decision tools. However, the adequacy of such tools is not clear. This paper investigates the foundations of maximin, minmax regret, and competitive ratio, three central qualitative decision criteria, by characterizing those behaviors which could result from their use.

I consider issues in distributed computation that should be of relevance to game theory. In particular, I focus on (a) representing knowledge and uncertainty, (b) dealing with failures, and (c) specification of mechanisms. Journal of Economic Literature Classification Numbers: D80, D83. 1

This paper focuses on the role that social norms play in the selection of equilibrium points seen as social conventions under unforeseen contingencies – that is, their role in the emergence of regularities of behavior which are selfenforcing and effectively adhered to by bounded rational agents due to their self-policing incentives. Differently stated, given a set of game situations imperfectly described, we want to understand how general and abstract norms provide at least the starting point for a norm-based equilibrium selection reasoning procedure which in the end will be able to determine which equilibrium point, belonging to perfectly described games, will be played as the unique solution of each imperfectly described game. In order to solve such a problem we introduces a selection process based on the reformulation of default logic in terms of possibility theory.