Marco Schaerf

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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)
Knowledge-based systems must be able to “intelligently” manage a large amount of information coming from different sources and at different moments in time. Intelligent systems must be able to cope with a changing world by adopting a “principled” strategy. Many formalisms have been put forward in the AI and DB literature to address this problem. Among them,(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)
We argue that essential facets of Web services, and especially those useful to understand their interaction, can be described using process-algebraic notations. Web service description and execution languages such as BPEL are essentially process description languages; they are based on primitives for behaviour description and message exchange which can also(More)
In this paper we address a specific computational aspect of belief revision: The size of the propositional formula obtained by means of the revision of a formula with a new one. In particular, we focus on the size of the smallest formula equivalent to the revised knowledge base. The main result of this paper is that not all formalizations of belief revision(More)
Some computationally hard problems –e.g., deduction in logical knowledge bases– are such that part of an instance is known well before the rest of it, and remains the same for several subsequent instances of the problem. In these cases, it is useful to preprocess off-line this known part so as to simplify the remaining on-line problem. In this paper we(More)