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<lb>Problems in logic are well-known to be hard to solve in the worst case. Two<lb>di erent strategies for dealing with this aspect are known from the literature:<lb>language restriction and theory approximation.<lb>In this paper we are concerned with the second strategy. Our main goal<lb>is to de ne a semantically well-founded logic for approximate(More)
The high computational complexity of advanced reasoning tasks such as belief revision and planning calls for efficient and reliable algorithms for reasoning problems harder than NP. In this paper we propose Evaluate, an algorithm for evaluating Quantified Boolean Formulae, a language that extends propositional logic in a way such that many advanced forms of(More)
The high computational complexity of advanced reasoning tasks such as reasoning about knowledge and planning calls for efficient and reliable algorithms for reasoning problems harder than NP. In this paper we propose Evaluate, an algorithm for evaluating quantified Boolean formulae (QBFs). Algorithms for evaluation of QBFs are suitable for experimental(More)
Knowledge compilation is an AI technique for addressing computationally demanding reasoning problems. In this paper we survey recent results in knowledge compilation of propositional knowledge bases. We first define and limit the scope of such a technique, then we survey exact and approximate knowledge compilation methods. We include a discussion of(More)
We present a compiler that translates a problem specification into a propositional satisfiability test (SAT). Problems are specified in a logic-based language, called NP-SPEC, which allows the definition of complex problems in a highly declarative way, and whose expressive power is such as to capture all problems which belong to the complexity class NP. The(More)