A fuzzy logic and default reasoning model of social norm and equilibrium selection in games under unforeseen contingencies

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.

[1]  Raymond Reiter,et al.  A Logic for Default Reasoning , 1987, Artif. Intell..

[2]  Raymond Reiter,et al.  On Interacting Defaults , 1981, IJCAI.

[3]  Kenneth G. Binmore,et al.  Essays on Foundations of Game Theory , 1982 .

[4]  R. Selten.  A general theory of equilibrium selection in games. Chapter 7: a bargaining problem with transaction costs on one side , 1984 .

[5]  Sérgio Ribeiro da Costa Werlang,et al.  Common knowledge and game theory , 1986 .

[6]  Ken Binmore,et al.  Modeling Rational Players: Part I , 1987, Economics and Philosophy.

[7]  A theory of rational decision in games , 1987, Erkenntnis.

[8]  Hector Geffner,et al.  Default reasoning - causal and conditional theories , 1992 .

[9]  Didier Dubois,et al.  Representing Default Rules in Possibilistic Logic , 1992, KR.

[10]  Didier Dubois,et al.  Mathematical models for handling partial knowledge in artificial intelligence , 1995 .

[11]  Didier Dubois,et al.  Possibilistic logic and plausible inference , 1995 .

[12]  Ronald Fagin,et al.  Reasoning about knowledge , 1995 .

[13]  Didier Dubois,et al.  Possibility Theory as a Basis for Qualitative Decision Theory , 1995, IJCAI.

[14]  R. Sugden.  A Theory of Focal Points , 1995 .

[15]  Eulalia Szmidt,et al.  Fuzzy thinking. The new science of fuzzy logic , 1996 .

[16]  D. Dubois,et al.  Fuzzy sets in approximate reasoning: a personal view , 1996 .

[17]  D. Dubois,et al.  Decision-making under ordinal preferences and uncertainty , 1997 .

[18]  Didier Dubois,et al.  Nonmonotonic Reasoning, Conditional Objects and Possibility Theory , 1997, Artif. Intell..

[19]  Ronen I. Brafman,et al.  Modeling Agents as Qualitative Decision Makers , 1997, Artif. Intell..

[20]  L. Samuelson.  Evolutionary Games and Equilibrium Selection , 1997 .

[21]  L. Zadeh.  Fuzzy sets as a basis for a theory of possibility , 1999 .

[22]  Mike Mesterton-Gibbons,et al.  The tracing procedure , 2000 .

[23]  L. Sacconi.  Economic Theory and the Social Contract of the Firm , 2000 .

[24]  John O.S. Kennedy,et al.  Qualitative dynamic programming for optimal timber cutting and conservation of Leadbeater's Possum , 2001 .

[25]  Stefano Moretti,et al.  Fuzzy Norms, Default Reasoning and Equilibrium Selection in Games under Unforeseen Contingencies , 2002 .

[26]  Lorenzo Sacconi,et al.  Incomplete Contracts and Corporate Ethics: A Game Theoretical Model Under Fuzzy Information , 2003 .

[27]  Polly S Nichols,et al.  Agreeing to disagree. , 2005, General dentistry.