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Otter: The CADE13 Competition Incarnations
 JOURNAL OF AUTOMATED REASONING
, 1997
"... This article discusses the two incarnations of Otter entered in the CADE13 Automated Theorem Proving Competition. Also presented are some historical background, a summary of applications that have led to new results in mathematics and logic, and a general discussion of Otter. ..."
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This article discusses the two incarnations of Otter entered in the CADE13 Automated Theorem Proving Competition. Also presented are some historical background, a summary of applications that have led to new results in mathematics and logic, and a general discussion of Otter.
Theoremproving by resolution as a basis for questionanswering systems, in
 Machine Intelligence, B. Meltzer and D. Michie, eds
, 1969
"... This paper shows how a questionanswering system can be constructed using firstorder logic as its language and a resolutiontype theoremprover as its deductive mechanism. A working computer program, qa3, based on these ideas is described. The performance of the program compares favorably with seve ..."
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This paper shows how a questionanswering system can be constructed using firstorder logic as its language and a resolutiontype theoremprover as its deductive mechanism. A working computer program, qa3, based on these ideas is described. The performance of the program compares favorably with several other general questionanswering systems. 1. QUESTION ANSWERING A questionanswering system accepts information about some subject areas and answers questions by utilizing this information. The type of questionanswering system considered in this paper is ideally one having the following features: 1. A language general enough to describe any reasonable questionanswering subjects and express desired questions and answers. 2. The ability to search efficiently the stored information and recognize items that are relevant to a particular query. 3. The ability to derive an answer that is not stored explicitly, but that is derivable by the use of moderate effort from the stored facts.
The Early History of Automated Deduction
 in Model Based Reasoning; Notes Workshop on ModelBased Reasoning
, 2001
"... this report. These are: 1. The one literal rule also known as the unit rule ..."
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this report. These are: 1. The one literal rule also known as the unit rule
The Applications of Theorem Proving to QuestionAnswering Systems
, 1969
"... This paper shows how a questionanswering system can use firstorder 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 ..."
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Cited by 27 (0 self)
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This paper shows how a questionanswering system can use firstorder 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 questionanswering programs. Methods are presented for solving state transformation problems. In addition to questionanswering, the program can do automatic programming
33 Basic Test Problems: A Practical Evaluation of Some Paramodulation Strategies
, 1996
"... 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 "ou ..."
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Cited by 24 (5 self)
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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, easytofind 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
Investigations in Model Elimination Based Theorem Proving
, 1992
"... Automated reasoning systems, also called automatic theorem provers, have been a focus of study since computer science expanded to include the study of symbolic computation in the 1950's. More recently, the socalled "logic programming" language Prolog has been the focus of much study that has genera ..."
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Cited by 6 (3 self)
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Automated reasoning systems, also called automatic theorem provers, have been a focus of study since computer science expanded to include the study of symbolic computation in the 1950's. More recently, the socalled "logic programming" language Prolog has been the focus of much study that has generated very efficient implementations of a language once noted for its expressive power, but now noted for its performance as well. The joining of Prolog technology with an early system of inference called Model Elimination led to the development of theorem proving systems with a very high rate of inference. This dissertation focuses on the study of automated reasoning based on Model Elimination. A theorem proving architecture and system called METEOR is described and is implemented that is the foundation of a reasoning system that runs on sequential computers, NUMA sharedmemory MIMD computers, and in a messagepassing distributed computing environment; this reasoning system has the highest r...
Proof Procedures for Logic Programming
, 1994
"... Proof procedures are an essential part of logic applied to artificial intelligence tasks, and form the basis for logic programming languages. As such, many of the chapters throughout this handbook utilize, or study, proof procedures. The study of proof procedures that are useful in artificial intell ..."
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Proof procedures are an essential part of logic applied to artificial intelligence tasks, and form the basis for logic programming languages. As such, many of the chapters throughout this handbook utilize, or study, proof procedures. The study of proof procedures that are useful in artificial intelligence would require a large book so we focus on proof procedures that relate to logic programming. We begin with the resolution procedures that influenced the definition of SLDresolution, the procedure upon which Prolog is built. Starting with the general resolution procedure we move through linear resolution to a very restricted linear resolution, SLresolution, which actually is not a resolution restriction, but a variant using an augmented logical form. (SLresolution actually is a derivative of the Model Elimination procedure, which was developed independently of resolution.) We then consider logic programming itself, reviewing SLDresolution and then describing a general criterion for ...
Ordered Resolution vs. Connection Graph Resolution
"... . Connection graph resolution (cgresolution) was introduced by Kowalski as a means of restricting the search space of resolution. Several researchers expected unrestricted connection graph (cg) resolution to be strongly complete until Eisinger proved that it was not. In this paper, ordered reso ..."
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. Connection graph resolution (cgresolution) was introduced by Kowalski as a means of restricting the search space of resolution. Several researchers expected unrestricted connection graph (cg) resolution to be strongly complete until Eisinger proved that it was not. In this paper, ordered resolution is shown to be a special case of cgresolution, and that relationship is used to prove that ordered cgresolution is strongly complete. On the other hand, ordered resolution provides little insight about completeness of rst order cgresolution and little about the establishment of strong completeness from completeness. A rst order version of Eisinger's cyclic example is presented, illustrating the diculties with rst order cg resolution. But resolution with selection functions does yield a simple proof of strong cgcompleteness for the unitrefutable class. 1