This paper shows how an extension of the resolution proof procedure can be used to construct problem solutions. The extended proof procedure can solve problems involving state transformations. The paper explores several alternate problem representations and provides a discussion of solutions to sample problems including the "Monkey and Bananas " puzzle and the 'Tower of Hanoi " puzzle. The paper exhibits solutions to these problems obtained by QA3, a computer program bused on these theorem-proving methods. In addition, the paper shows how QA3 can write simple computer programs and can solve practical problems for a simple robot. Key Words: Theorem proving, resolution, problem solving, automatic programming, program writing, robots, state transformations, question answering. Automatic theorem proving by the resolution proof procedure § represents perhaps the most powerful known method for automatically determining the validity of a statement of first-order logic. In an earlier paper Green and Raphael" illustrated how an extended resolution procedure can be used as a question answerer—e.g., if the statement (3x)P(x) can be shown to follow from a set of axioms by the resolution proof procedure, then the extended proof procedure will find or construct an x that satisfies P(x). This earlier paper (1) showed how one can axiomatize simple question-answering subjects, (2) described a question-answering program called QA2 based on this procedure, and (3) presented examples of simple question-answering dialogues with QA2. In a more recent paper " the author (1) presents the answer construction method in detail and proves its correctness, (2) describes the latest version of the program, QA3, and (3) introduces state-transformation methods into the constructive proof formalism. In addition to the question-answering applications illustrated in these earlier papers, QA3 has been used as an SRI robot 4 problem solver and as an automatic

A policy describes the conditions under which an action is permitted or forbidden. We show that a fragment of (multi-sorted) first-order logic can be used to represent and reason about policies. Because we use first-order logic, policies have a clear syntax and semantics. We show that further restricting the fragment results in a language that is still quite expressive yet is also tractable. More precisely, questions about entailment, such as `May Alice access the file?', can be answered in time that is a low-order polynomial (indeed, almost linear in some cases), as can questions about the consistency of policy sets. We also give a brief overview of a prototype that we have built whose reasoning engine is based on the logic and whose interface is designed for non-logicians, allowing them to enter both policies and background information, such as `Alice is a student', and to ask questions about the policies.

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Introduction Many researchers who study the theoretical aspects of inference systems believe that if inference rule A is complete and more restrictive than inference rule B, then the use of A will lead more quickly to proofs than will the use of B. The literature contains statements of the sort "our rule is complete and it heavily prunes the search space; therefore it is efficient". 2 These positions are highly questionable and indicate that the authors have little or no experience with the practical use of automated inference systems. Restrictive rules (1) can block short, easy-to-find proofs, (2) can block proofs involving simple clauses, the type of clause on which many practical searches focus, (3) can require weakening of redundancy control such as subsumption and demodulation, and (4) can require the use of complex checks in deciding whether such rules should be applied. The only way to determ

This paper shows how a question-answering system can use first-order logic as its language and an automatic theorem prover, based upon the resolution inference principle, as its deductive mechanism. The resolution proof procedure is extended to a constructive proof procedure. An answer construction algorithm is given whereby the system is able not only to produce yes or no answers but also to find or construct an object satisfying a specified condition. A working computer program, QA3, based on these ideas, is described. The performance of the program, illustrated by extended examples, compares favorably with several other question-answering programs. Methods are presented for solving state transformation problems. In addition to question-answering, the program can do automatic programming

We introduce the distributed theorem prover Peers-mcd for networks of workstations. Peers-mcd is the parallelization of the Argonne prover EQP, according to our Clause-Diffusion methodology for distributed deduction. The new features of Peers-mcd include the AGO (Ancestor-Graph Oriented) heuristic criteria for subdividing the search space among parallel processes. We report the performance of Peers-mcd on several experiments, including problems which require days of sequential computation. In these experiments Peersmcd achieves considerable, sometime super-linear, speed-up over EQP. We analyze these results by examining several statistics produced by the provers. The analysis shows that the AGO criteria partitions the search space effectively, enabling Peers-mcd to achieve super-linear speed-up by parallel search. 1 Introduction Distributed deduction is concerned with the problem of proving difficult theorems by distributing the work among networked computers. The motivation is to st...

The COCOLOG system is a partially ordered family of first order logical theories that describe the controlled evolution of the state of a given partially observered finite machine M. Following the review of the general theory of COCOLOG, the notion of Markovian fragments MTh k ,k 1, of full COCOLOG theories Th k is presented. These fragments enjoy the property of having axiom set of fixed size over time. MTh k and Th k have the virtually same state estimation and control power. Next, a newly developed automatic theorem proving software called Blitzenstrum is described and some applications Blitzenstrum 5.0 to the logic control of a stylized elevator problem are presented.

In this paper, the authors describe their initial investigations in computational metaphysics. Our method is to implement axiomatic metaphysics in an automated reasoning system. In this paper, we describe what we have discovered when the theory of abstract objects is implemented in prover9 (a first-order automated reasoning system which is the successor to otter). After reviewing the second-order, axiomatic theory of abstract objects, we show (1) how to represent a fragment of that theory in prover9's first-order syntax, and (2) how prover9 then finds proofs of interesting theorems of metaphysics, such as that every possible world is maximal. We conclude the paper by discussing some issues for further research.

Abstract. We give an approach for deciding satisfiability of equality logic formulas (E-SAT) in conjunctive normal form. Central in our approach is a single proof rule called equality resolution (ER). For this single rule we prove soundness and completeness. Based on this rule we propose a complete procedure for E-SAT and prove its correctness. Applying our procedure on a variation of the pigeon hole formula yields a polynomial complexity contrary to earlier approaches to E-SAT. Parts of the theory we developed for proving completeness of the proof rule and the algorithm are of interest in itself: we give techniques for removing clauses preserving unsatisfiability, and we give a general theorem globalizing a local commutation criterion for different proof systems.

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