%0 Conference Paper %B Proceedings of the International Joint Conference on Artificial Intelligence %D 2007 %T A general framework for reasoning about inconsistency %A V.S. Subrahmanian %A Amgoud,L. %X Numerous logics have been developed for reason-ing about inconsistency which differ in (i) the logic to which they apply, and (ii) the criteria used to draw inferences. In this paper, we propose a gen- eral framework for reasoning about inconsistency in a wide variety of logics including ones for which inconsistency resolution methods have not yet been studied (e.g. various temporal and epistemic log- ics). We start with Tarski and Scott’s axiomatiza- tion of logics, but drop their monotonicity require- ments that we believe are too strong for AI. For such a logic L, we define the concept of an option. Options are sets of formulas in L that are closed and consistent according to the notion of consequence and consistency in L. We show that by defining an appropriate preference relation on options, we can capture several existing works such as Brewka’s subtheories. We also provide algorithms to com- pute most preferred options. %B Proceedings of the International Joint Conference on Artificial Intelligence %P 599 - 604 %8 2007/// %G eng