Results 1  10
of
64
Hard and Easy Distributions of SAT Problems
, 1992
"... We report results from largescale experiments in satisfiability testing. As has been observed by others, testing the satisfiability of random formulas often appears surprisingly easy. Here we show that by using the right distribution of instances, and appropriate parameter values, it is possible to ..."
Abstract

Cited by 252 (18 self)
 Add to MetaCart
We report results from largescale experiments in satisfiability testing. As has been observed by others, testing the satisfiability of random formulas often appears surprisingly easy. Here we show that by using the right distribution of instances, and appropriate parameter values, it is possible to generate random formulas that are hard, that is, for which satisfiability testing is quite difficult. Our results provide a benchmark for the evaluation of satisfiabilitytesting procedures. Introduction Many computational tasks of interest to AI, to the extent that they can be precisely characterized at all, can be shown to be NPhard in their most general form. However, there is fundamental disagreement, at least within the AI community, about the implications of this. It is claimed on the one hand that since the performance of algorithms designed to solve NPhard tasks degrades rapidly with small increases in input size, something will need to be given up to obtain acceptable behavior....
Improvements To Propositional Satisfiability Search Algorithms
, 1995
"... ... quickly across a wide range of hard SAT problems than any other SAT tester in the literature on comparable platforms. On a Sun SPARCStation 10 running SunOS 4.1.3 U1, POSIT can solve hard random 400variable 3SAT problems in about 2 hours on the average. In general, it can solve hard nvariable ..."
Abstract

Cited by 176 (0 self)
 Add to MetaCart
... quickly across a wide range of hard SAT problems than any other SAT tester in the literature on comparable platforms. On a Sun SPARCStation 10 running SunOS 4.1.3 U1, POSIT can solve hard random 400variable 3SAT problems in about 2 hours on the average. In general, it can solve hard nvariable random 3SAT problems with search trees of size O(2 n=18:7 ). In addition to justifying these claims, this dissertation describes the most significant achievements of other researchers in this area, and discusses all of the widely known general techniques for speeding up SAT search algorithms. It should be useful to anyone interested in NPcomplete problems or combinatorial optimization in general, and it should be particularly useful to researchers in either Artificial Intelligence or Operations Research.
Compiling Constraints in clp(FD)
, 1996
"... We present the clp(FD) system: a Constraint Logic Programming language with finite domain constraints... ..."
Abstract

Cited by 174 (24 self)
 Add to MetaCart
We present the clp(FD) system: a Constraint Logic Programming language with finite domain constraints...
Algorithms for the Satisfiability (SAT) Problem: A Survey
 DIMACS Series in Discrete Mathematics and Theoretical Computer Science
, 1996
"... . The satisfiability (SAT) problem is a core problem in mathematical logic and computing theory. In practice, SAT is fundamental in solving many problems in automated reasoning, computeraided design, computeraided manufacturing, machine vision, database, robotics, integrated circuit design, compute ..."
Abstract

Cited by 145 (3 self)
 Add to MetaCart
(Show Context)
. The satisfiability (SAT) problem is a core problem in mathematical logic and computing theory. In practice, SAT is fundamental in solving many problems in automated reasoning, computeraided design, computeraided manufacturing, machine vision, database, robotics, integrated circuit design, computer architecture design, and computer network design. Traditional methods treat SAT as a discrete, constrained decision problem. In recent years, many optimization methods, parallel algorithms, and practical techniques have been developed for solving SAT. In this survey, we present a general framework (an algorithm space) that integrates existing SAT algorithms into a unified perspective. We describe sequential and parallel SAT algorithms including variable splitting, resolution, local search, global optimization, mathematical programming, and practical SAT algorithms. We give performance evaluation of some existing SAT algorithms. Finally, we provide a set of practical applications of the sat...
Directed Hypergraphs And Applications
, 1992
"... We deal with directed hypergraphs as a tool to model and solve some classes of problems arising in Operations Research and in Computer Science. Concepts such as connectivity, paths and cuts are defined. An extension of the main duality results to a special class of hypergraphs is presented. Algorith ..."
Abstract

Cited by 141 (5 self)
 Add to MetaCart
We deal with directed hypergraphs as a tool to model and solve some classes of problems arising in Operations Research and in Computer Science. Concepts such as connectivity, paths and cuts are defined. An extension of the main duality results to a special class of hypergraphs is presented. Algorithms to perform visits of hypergraphs and to find optimal paths are studied in detail. Some applications arising in propositional logic, AndOr graphs, relational data bases and transportation analysis are presented. January 1990 Revised, October 1992 ( * ) This research has been supported in part by the "Comitato Nazionale Scienza e Tecnologia dell'Informazione", National Research Council of Italy, under Grant n.89.00208.12, and in part by research grants from the National Research Council of Canada. 1 Dipartimento di Informatica, Università di Pisa, Italy 2 Département d'Informatique et de Recherche Opérationnelle, Université de Montréal, Canada 2 INTRODUCTION Hypergraphs, a generaliz...
Finding Hard Instances of the Satisfiability Problem: A Survey
, 1997
"... . Finding sets of hard instances of propositional satisfiability is of interest for understanding the complexity of SAT, and for experimentally evaluating SAT algorithms. In discussing this we consider the performance of the most popular SAT algorithms on random problems, the theory of average case ..."
Abstract

Cited by 130 (1 self)
 Add to MetaCart
. Finding sets of hard instances of propositional satisfiability is of interest for understanding the complexity of SAT, and for experimentally evaluating SAT algorithms. In discussing this we consider the performance of the most popular SAT algorithms on random problems, the theory of average case complexity, the threshold phenomenon, known lower bounds for certain classes of algorithms, and the problem of generating hard instances with solutions.
Generating Hard Satisfiability Problems
 Artificial Intelligence
, 1996
"... We report results from largescale experiments in satisfiability testing. As has been observed by others, testing the satisfiability of random formulas often appears surprisingly easy. Here we show that by using the right distribution of instances, and appropriate parameter values, it is possible ..."
Abstract

Cited by 109 (2 self)
 Add to MetaCart
We report results from largescale experiments in satisfiability testing. As has been observed by others, testing the satisfiability of random formulas often appears surprisingly easy. Here we show that by using the right distribution of instances, and appropriate parameter values, it is possible to generate random formulas that are hard, that is, for which satisfiability testing is quite difficult. Our results provide a benchmark for the evaluation of satisfiabilitytesting procedures. In Artificial Intelligence, 81 (19996) 1729. 1 Introduction Many computational tasks of interest to AI, to the extent that they can be precisely characterized at all, can be shown to be NPhard in their most general form. However, there is fundamental disagreement, at least within the AI community, about the implications of this. It is claimed on the one hand that since the performance of algorithms designed to solve NPhard tasks degrades rapidly with small increases in input size, something ...
Branching Rules for Satisfiability
 Journal of Automated Reasoning
, 1995
"... Recent experience suggests that branching algorithms are among the most attractive for solving propositional satisfiability problems. A key factor in their success is the rule they use to decide on which variable to branch next. We attempt to explain and improve the performance of branching rules wi ..."
Abstract

Cited by 82 (2 self)
 Add to MetaCart
(Show Context)
Recent experience suggests that branching algorithms are among the most attractive for solving propositional satisfiability problems. A key factor in their success is the rule they use to decide on which variable to branch next. We attempt to explain and improve the performance of branching rules with an empirical modelbuilding approach. One model is based on the rationale given for the JeroslowWang rule, variations of which have performed well in recent work. The model is refuted by carefully designed computational experiments. A second model explains the success of the JeroslowWang rule, makes other predictions confirmed by experiment, and leads to the design of branching rules that are clearly superior to JeroslowWang. Recent computational studies [2, 7, 13, 21] suggest that branching algorithms are among the most attractive for solving the propositional satisfiability problem. An important factor in their successperhaps the dominant factoris the branching rule they use [...
Propositional Defeasible Logic has Linear Complexity
 of Logic Programming
, 2001
"... Defeasible logic is a rulebased nonmonotonic logic, with both strict and defeasible rules, and a priority relation on rules. We show that inference in the propositional form of the logic can be performed in linear time. This contrasts markedly with most other propositional nonmonotonic logics, i ..."
Abstract

Cited by 82 (6 self)
 Add to MetaCart
Defeasible logic is a rulebased nonmonotonic logic, with both strict and defeasible rules, and a priority relation on rules. We show that inference in the propositional form of the logic can be performed in linear time. This contrasts markedly with most other propositional nonmonotonic logics, in which inference is intractable. 1 Introduction Mostwork in nonmonotonicreasoning has focussed on languages for whichpropositional inference is not tractable. Sceptical default reasoning is \Pi p 2 hard, even for very simple classes of default rules, as is sceptical autoepistemic reasoning and propositional circumscription. The complexity of sceptical inference from logic programs with negationasfailure varies according to the semantics of negation. For both the stable model semantics and the Clark completion, sceptical inference is coNPhard. See [13, 9] for more details. Although such languages are very expressive, and this expressiveness has been exploited in answerset progra...
Efficient Defeasible Reasoning Systems
 International Journal of Artificial Intelligence Tools
, 2001
"... For many years, the nonmonotonic reasoning community has focussed on highly expressive logics. Such logics have tumed out to be computationally expensive, and have given little support to the practical use of nonmonotonic reasoning. In this work we discuss defeasible logic, a lessexpressive but ..."
Abstract

Cited by 69 (20 self)
 Add to MetaCart
For many years, the nonmonotonic reasoning community has focussed on highly expressive logics. Such logics have tumed out to be computationally expensive, and have given little support to the practical use of nonmonotonic reasoning. In this work we discuss defeasible logic, a lessexpressive but more efficient nonmonotonic logic. We report on two new implemented systems for defeasible logic: a query answering system employing a backwardchaining approach, and a forwardchaining implementation that computes all conclusions. Our experimental evaluation demonstrates that the systems can deal with large theories (up to hundreds of thousands of rules). We show that defeasible logic has linear complexity, which contrasts markedly with most other nonmonotonic logics and helps to explain the impressive experimental results. We believe that defeasible logic, with its eficiency and simplicity, is a good candidate to be used as a modelling language for practical applications, including modelling of regulations and business rules. 1