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PARTHENON: A Parallel Theorem Prover for Non.Horn Clauses
"... The goal of the PARTHENON project is to develop a generalpurpose, parallel, resolution theorem prover that will run on shared memory multiprocessors. The major issues that the project addresses are the selection of an appropriate resolution proof procedure, the partitioning of the search so as to ..."
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is necessary. For our prototype implementation we deliberately chose a very simple strategy for allocating work to processors in which a global priority queue is used for maintaining resolvents. The resolvents are ordered in the queue according to a heuristic value. Each processor withdraws the best clause
A Parallel Theorem Prover for NonHorn Causes Soumitra Bose
"... Parthenon: a parallel theorem prover for nonHorn clauses ..."
NonHorn Magic Sets to Incorporate Topdown Inference into Bottomup Theorem Proving
, 1997
"... We present a new method, called nonHorn magic sets (NHM), to enhance forward reasoning provers by combining topdown and bottomup computations. This method is a natural extension of Horn magic sets and is applicable to rangerestricted nonHorn clauses. We show two types of transformations to get n ..."
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Cited by 4 (1 self)
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We present a new method, called nonHorn magic sets (NHM), to enhance forward reasoning provers by combining topdown and bottomup computations. This method is a natural extension of Horn magic sets and is applicable to rangerestricted nonHorn clauses. We show two types of transformations to get
On Computing Minimal Models
 Annals of Mathematics and Artificial Intelligence
, 1993
"... This paper addresses the problem of computing the minimal models of a given CNF propositional theory. We present two groups of algorithms. Algorithms in the first group are efficient when the theory is almost Horn, that is, when there are few nonHorn clauses and/or when the set of all literals that ..."
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Cited by 23 (1 self)
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This paper addresses the problem of computing the minimal models of a given CNF propositional theory. We present two groups of algorithms. Algorithms in the first group are efficient when the theory is almost Horn, that is, when there are few nonHorn clauses and/or when the set of all literals
Computing Horn strong backdoor sets thanks to local search
 ICTAI’06, 0:139–143, 2006. ISSN
"... In this paper a new approach for computing Strong Backdoor sets of boolean formula in conjunctive normal form (CNF) is proposed. It makes an original use of local search techniques for finding an assignment leading to a largest renamable Horn subformula of a given CNF. More precisely, at each step, ..."
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Cited by 9 (0 self)
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, preference is given to variables such that when assigned to the opposite value lead to the smallest number of remaining nonHorn clauses. Consequently, if no positive or non Horn clauses remain in the formula, our approach answer the satisfiability of the original formula; otherwise, a smallest nonHorn sub
1 ASimple Test Improves Checking Satisfiability
"... Abstract. In many practical cases satisfiability of a set of clauses can be decided before an interpretation is found that satisfies all clauses of the set. We present a test for such an early discovery of satisfiability, EDS,and develop an algorithm, IDP,incorporating EDS and a branching heuristics ..."
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heuristics related to this test. IDP was implemented and tested on a wide variety of instances showing a high performance and stability with respect to changing proportion of nonHorn clauses. 1.
Inverse Entailment for Full Clausal Theories
 In: LICS2001 Workshop on Logic and Learning
, 2001
"... This paper shows a sound and complete method for inverse entailment in inductive logic programming. We show that inverse entailment can be computed with a resolution method for consequencefinding. In comparison with previous work, induction via consequencefinding is sound and complete for finding h ..."
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Cited by 6 (0 self)
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hypotheses from full clausal theories, and can be used for inducing not only definite clauses but also nonHorn clauses and integrity constraints.
A nearHorn Prolog for Compilation
 Computational Logic: Essays in Honor of Alan
, 1989
"... NearHorn Prolog is a logic programming language which extends Prolog to handle nonHorn clauses. It was designed with the goal of minimizing the performance loss for programs with very few nonHorn clauses, while preserving the Prolog format. In this paper, we present a version of nearHorn Prolog ..."
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Cited by 10 (4 self)
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NearHorn Prolog is a logic programming language which extends Prolog to handle nonHorn clauses. It was designed with the goal of minimizing the performance loss for programs with very few nonHorn clauses, while preserving the Prolog format. In this paper, we present a version of nearHorn Prolog
1 LOGIC PROGRAMMING IN NEURAL NETWORKS
"... Logic programming is carried out on a neural network. A higherorder Hopfield neural network is used to minimise logical inconsistency in interpretations of logic clauses or programs. The connection strengths are defined from the logic program; the network relaxes to neural states corresponding to a ..."
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to a valid (or nearvalid) interpretation. ‘Creativity ’ can be thought of as the crossing of configurational energy barriers to arrive at alternative interpretations. The formalism allows the incorporation of nonmonotonicity; nonintegral degrees of truth in rules; and nonHorn clauses. Hebbian
On the Relationship Between NonHorn Magic Sets and Relevancy Testing
 PROC. CADE'98
, 1998
"... Modelgeneration based theorem provers such as SATCHMO and MGTP su#er from a combinatorial explosion of the search space caused by clauses irrelevant to the goal (negative clause) to be solved. To avoid this, two typical methods have been proposed. One is relevancy testing implemented in SATCHMORE b ..."
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Cited by 5 (1 self)
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by Loveland et al., and the other is nonHorn magic sets that are the extension of Horn magic sets and used for MGTP. In this paper, we define the concept of weak relevancy testing, which somewhat relaxes the relevancy testing constraint. Then, we analyze the relationship between nonHorn magic sets and weak
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