Titlebook: Resolution Proof Systems; An Algebraic Theory Zbigniew Stachniak Book 1996 Kluwer Academic Publishers 1996 algebra.artificial intelligence.

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https://doi.org/10.1007/978-94-009-1677-7algebra; artificial intelligence; automated reasoning; intelligence; logic; nonmonotonic reasoning; proof;

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Propositional Resolution Logics,cs with strong resolution counterparts. We also study resolution counterparts of disjunctive logics and show that in the presence of disjunction, the deductive process can be based on a single-conclusion variant of the resolution rule.

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Efficiency of the Deductive Process,initely many applications of the inference rules. This property, however, does not provide us with any information as to how the resolution and the transformation rules should be utilized efficiently during the deductive process.

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Theorem Proving Strategies,In Chapter 4 we discussed ways of improving the efficiency of resolution based deductive process by minimizing the length of resolvents and by simplifying the termination test. In this chapter we focus on theorem proving strategies — the speed-up techniques for controlling and directing the deductive process of an automated reasoning system.

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Resolution Circuits,In Chapters 4 and 5 we discussed methods and strategies for an efficient implementation of the deductive process. In this chapter we continue this discussion; we introduce and study resolution circuits — multi-resolution proof system representations of resolution logics.

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First-Order Resolution Proof Systems,In this chapter we extend the theory of propositional resolution proof systems to finitely-valued first-order logics. Throughout this chapter we assume that all . logics under consideration have infinitely many ground atomic formulas and that these logics are defined by proper and well-connected matrices.

Indict

Propositional Resolution Proof Systems,normal form’. Neither the relation between classical and non-classical automated proof methods nor the problem of ‘clausal’ versus ‘non-clausal’ proof procedures will be discussed in depth in this book. For the discussion on these and related topics the reader is referred to [19, 73, 75].

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Book 1996nic as well asnonmonotonic reasoning. .This book is aimed primarily at researchers and graduate students inartificial intelligence, symbolic and computational logic. Thematerial is suitable as a reference book for researchers and as a textbook for graduate courses on the theoretical aspects of automatedreasoning and computational logic.