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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 ..."
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Cited by 144 (3 self)
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. 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...
The Consistent Labeling Problem: Part I
 IEEE Trans. Pattern Anal. Mach. Intell
, 1979
"... AbstractIn this first part of a twopart paper we introduce a general consistent labeling problem based on a unit constraint relation T containing Ntuples of units which constrain one another, and a compatibility relation R containing Ntuples of unitlabel pairs specifying which Ntuples of uni ..."
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Cited by 33 (3 self)
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AbstractIn this first part of a twopart paper we introduce a general consistent labeling problem based on a unit constraint relation T containing Ntuples of units which constrain one another, and a compatibility relation R containing Ntuples of unitlabel pairs specifying which Ntuples of units are compatible with which Ntuples of labels. We show that Latin square puzzles, finding Nary relations, graph or automata homomorphisms, graph colorings, as well as determining satisfiability of propositional logic statements and solving scene and edge labeling problems, are all special cases of the general consistent labeling problem. We then discuss the various approaches that researchers have used to speed up the tree search required to find consistent labelings. Each of these approaches uses a particular lookahead operator to help eliminate backtracking in the tree search. Finally, we define the 4KP twoparameter class of lookahead operators which includes, as special cases, the operators other researchers have used. Index TermsBacktracking, consistent labeling, graph coloring, homorphisms, isomorphisms, lookahead operators, matching, Nary relations, relaxation, scene analysis, subgraph, tree search. 1.
Parametricity as a Notion of Uniformity in Reflexive Graphs
, 2002
"... data types embody uniformity in the form of information hiding. Information hiding enforces the uniform treatment of those entities that dier only on hidden information. ..."
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Cited by 12 (3 self)
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data types embody uniformity in the form of information hiding. Information hiding enforces the uniform treatment of those entities that dier only on hidden information.
Topologies of learning and development
 NEW IDEAS IN PSYCHOLOGY
, 1996
"... How systems can represent and how systems can learn are two central problems in the study of cognition. Conventional contemporary approaches to these problems are vitiated by a shared error in their presuppositions about representation. Consequently, such approaches share further errors about the so ..."
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Cited by 9 (5 self)
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How systems can represent and how systems can learn are two central problems in the study of cognition. Conventional contemporary approaches to these problems are vitiated by a shared error in their presuppositions about representation. Consequently, such approaches share further errors about the sorts of architectures that are required to support either representation or learning. We argue that the architectural requirements for genuine representing systems lead to architectural characteristics that are necessary (though not sufficient) for heuristic learning and development. These architectural constraints, in turn, explain properties of the functioning of the central nervous system that remain inexplicable for standard approaches.
S0732118X(96)000153 TOPOLOGIES OF LEARNING AND DEVELOPMENT
"... AbstractHow systems can represent and how systems can learn are two central problems in the study of cognition. Conventional contemporary approaches to these problems are vitiated by a shared error in their presuppositions about representation. Consequently, such approaches share further errors ab ..."
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AbstractHow systems can represent and how systems can learn are two central problems in the study of cognition. Conventional contemporary approaches to these problems are vitiated by a shared error in their presuppositions about representation. Consequently, such approaches share further errors about the sorts of architectures that are required to support either representation or learning. We argue that the architectural requirements for genuine representing systems lead to architectural characteristics that are necessary (though not sufficient) for heuristic learning and development. These architectural constraints, in turn, explain properties of the functioning of the central nervous system that remain inexplicable for standard approaches. Copyright © 1996 Elsevier Science Ltd