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Partial Constraint Satisfaction
, 1992
"... . A constraint satisfaction problem involves finding values for variables subject to constraints on which combinations of values are allowed. In some cases it may be impossible or impractical to solve these problems completely. We may seek to partially solve the problem, in particular by satisfying ..."
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Cited by 471 (21 self)
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. A constraint satisfaction problem involves finding values for variables subject to constraints on which combinations of values are allowed. In some cases it may be impossible or impractical to solve these problems completely. We may seek to partially solve the problem, in particular by satisfying
Adaptive Constraint Satisfaction
 WORKSHOP OF THE UK PLANNING AND SCHEDULING
, 1996
"... Many different approaches have been applied to constraint satisfaction. These range from complete backtracking algorithms to sophisticated distributed configurations. However, most research effort in the field of constraint satisfaction algorithms has concentrated on the use of a single algorithm fo ..."
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Cited by 952 (43 self)
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Many different approaches have been applied to constraint satisfaction. These range from complete backtracking algorithms to sophisticated distributed configurations. However, most research effort in the field of constraint satisfaction algorithms has concentrated on the use of a single algorithm
Analogical Mapping by Constraint Satisfaction
 COGNITIVE SCIENCE 13, 295 (1989)
, 1989
"... A theory of analogical mopping between source and target analogs based upon interacting structural, semantic, and pragmatic constraints is proposed here. The structural constraint of fsomorphfsm encourages mappings that maximize the consistency of relational corresondences between the elements of th ..."
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Cited by 397 (29 self)
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the anology Is being used. The theory is implemented in a computer progrom called ACME (Analogical Constraint Mapping Engine), which represents constraints by means of a network of supporting and competing hypotheses regarding what elements to map. A coop erative algorithm for parallel constraint satisfaction
Algorithms for ConstraintSatisfaction Problems: A Survey
, 1992
"... A large number of problems in AI and other areas of computer science can be viewed as special cases of the constraintsatisfaction problem. Some examples are machine vision, belief maintenance, scheduling, temporal reasoning, graph problems, floor plan design, the planning of genetic experiments, an ..."
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Cited by 449 (0 self)
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A large number of problems in AI and other areas of computer science can be viewed as special cases of the constraintsatisfaction problem. Some examples are machine vision, belief maintenance, scheduling, temporal reasoning, graph problems, floor plan design, the planning of genetic experiments
The logic of constraint satisfaction
, 1992
"... The constraint satisfaction problem (CSP) formalization has been a productive tool within Artificial Intelligence and related areas. The finite CSP (FCSP) framework is presented here as a restricted logical calculus within a space of logical representation and reasoning systems. FCSP is formulated i ..."
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Cited by 265 (5 self)
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The constraint satisfaction problem (CSP) formalization has been a productive tool within Artificial Intelligence and related areas. The finite CSP (FCSP) framework is presented here as a restricted logical calculus within a space of logical representation and reasoning systems. FCSP is formulated
Hybrid Algorithms for the Constraint Satisfaction Problem
 Computational Intelligence
, 1993
"... problem (csp), namely, naive backtracking (BT), backjumping (BJ), conflictdirected backjumping ..."
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Cited by 380 (8 self)
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problem (csp), namely, naive backtracking (BT), backjumping (BJ), conflictdirected backjumping
Valued constraint satisfaction problems: Hard and easy problems
 IJCAIâ€™95: PROCEEDINGS INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE
, 1995
"... In order to deal with overconstrained Constraint Satisfaction Problems, various extensions of the CSP framework have been considered by taking into account costs, uncertainties, preferences, priorities...Each extension uses a specific mathematical operator (+, max...) to aggregate constraint violat ..."
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Cited by 331 (42 self)
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In order to deal with overconstrained Constraint Satisfaction Problems, various extensions of the CSP framework have been considered by taking into account costs, uncertainties, preferences, priorities...Each extension uses a specific mathematical operator (+, max...) to aggregate constraint
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
 ARTIF. INTELL
, 1992
"... This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a valueorderin ..."
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Cited by 457 (6 self)
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This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a value
Constraint Satisfaction
 In In the MIT Encyclopedia of the Cognitive Sciences (MITECS
, 1991
"... to A, true to B, false to C and false to D, is a satisfying truth value assignment. The structure of a constraintnetwork is depicted by a constraint graph whose nodes represents the variables and anytwo nodes are connected if the corresponding variables participate in the same constraint. In the k ..."
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Cited by 16 (3 self)
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, default reasoning, and abduction, as well as in applications suchasscheduling, design, diagnosis, and temporal and spatial reasoning. In general, constraint satisfaction tasks are computationally intractable #NPhard# #see COMPUTATIONAL COMPLEXITY #. Techniques for pr
Contradicting Conventional Wisdom in Constraint Satisfaction
, 1994
"... . Constraint satisfaction problems have wide application in artificial intelligence. They involve finding values for problem variables where the values must be consistent in that they satisfy restrictions on which combinations of values are allowed. Two standard techniques used in solving such p ..."
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Cited by 228 (12 self)
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. Constraint satisfaction problems have wide application in artificial intelligence. They involve finding values for problem variables where the values must be consistent in that they satisfy restrictions on which combinations of values are allowed. Two standard techniques used in solving
Results 1  10
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