We propose a sound and complete satisfiability algorithm for propositional multi-context systems. In essence, the algorithm is a distribution policy built on top of local reasoning procedures, one for each context, which can be implemented by (a diversity of) customized state-of-the-art SAT solvers. The foremost intuition that has motivated our algorithm, and the very potential strength of contextual reasoning, is that of keeping reasoning as local as possible. In doing so, we improve on earlier established complexity results by Massacci. Moreover, our approach could be applied to enhance recent proposals by Amir and Mcilraith towards a new partition-based reasoning paradigm; particularly, our formalism allows for a more expressive description of interpartition (intercontextual) relations, and we provide an algorithm that is explicitly designed to deal with this expressiveness
Satisfiability for Propositional Contexts
Serafini, Luciano;Roelofsen, Floris
2004-01-01
Abstract
We propose a sound and complete satisfiability algorithm for propositional multi-context systems. In essence, the algorithm is a distribution policy built on top of local reasoning procedures, one for each context, which can be implemented by (a diversity of) customized state-of-the-art SAT solvers. The foremost intuition that has motivated our algorithm, and the very potential strength of contextual reasoning, is that of keeping reasoning as local as possible. In doing so, we improve on earlier established complexity results by Massacci. Moreover, our approach could be applied to enhance recent proposals by Amir and Mcilraith towards a new partition-based reasoning paradigm; particularly, our formalism allows for a more expressive description of interpartition (intercontextual) relations, and we provide an algorithm that is explicitly designed to deal with this expressivenessI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
