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35
Maintaining generalized arc consistency on adhoc nary boolean constraints
 IN ECAI06
, 2006
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Structuring Techniques for Constraint Satisfaction Problems
 In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence
, 1997
"... We present a structuring method for discrete constraint satisfaction problems (CSPs). It takes advantage of interchangeabilities to represent sets of equivalent values by metavalues and thus obtain more compact representations. Strongly related variables are clustered into metavariables to create ..."
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Cited by 14 (6 self)
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We present a structuring method for discrete constraint satisfaction problems (CSPs). It takes advantage of interchangeabilities to represent sets of equivalent values by metavalues and thus obtain more compact representations. Strongly related variables are clustered into metavariables to create occurrences of interchangeabilities. By iterative application, a CSP can be transformed into an hierarchy of equivalent CSPs, where each problem is significantly simpler than the original one. This structure is particularly advantageous when a large set of possible solutions must be inspected. 1 Introduction We consider binary CSPs defined by P = (X; D;C;R), where X = fX 1 ; : : : ; Xng is a set of variables, D = fD 1 ; : : : ; Dng a set of finite domains associated with the variables, C = fC 1 ; : : : ; Cm g a set of constraints, and R =fR ij ` D i \Theta D j for C ij applicable to X i and X j g a set of relations that define the value combinations allowed by the constraints. Solving s...
Constrained decision diagrams
 In Proceedings of the National Conference on Artificial Intelligence, AAAI05
, 2005
"... A general nary constraint is usually represented explicitly as a set of its solution tuples, which may need exponential space. In this paper, we introduce a new representation for general nary constraints called Constrained Decision Diagram (CDD). CDD generalizes BDDstyle representations and the ..."
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Cited by 12 (3 self)
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A general nary constraint is usually represented explicitly as a set of its solution tuples, which may need exponential space. In this paper, we introduce a new representation for general nary constraints called Constrained Decision Diagram (CDD). CDD generalizes BDDstyle representations and the main feature is that it combines constraint reasoning/consistency techniques with a compact data structure. We present an application of CDD for recording all solutions of a conjunction of constraints. Instead of an explicit representation, we can implicitly encode the solutions by means of constraint propagation. Our experiments confirm the scalability and demonstrate that CDDs can drastically reduce the space needed over explicit and ZBDD representations.
A Disjunctive Decomposition Control Schema for Constraint Satisfaction
 In Principles and Practice of Constraint Programming, 1st International Workshop, PPCP’93
, 1995
"... The paper presents a control schema for constraint satisfaction. Several algorithms, old and new, are formulated as instances of this schema by specifying different methods of problem decomposition. This formulation facilitates description and comparison of the algorithms and suggests directions for ..."
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Cited by 8 (1 self)
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The paper presents a control schema for constraint satisfaction. Several algorithms, old and new, are formulated as instances of this schema by specifying different methods of problem decomposition. This formulation facilitates description and comparison of the algorithms and suggests directions for further research. A new decomposition method is presented that is virtually guaranteed to reduce problem size, while always retaining at least one of the solutions to the original problem. 1
Neighborhood Interchangeability and Dynamic Bundling for NonBinary Finite CSPs
 In Joint Annual Workshop of ERCIM/CoLogNet on Constraint Solving and Constraint Logic Programming (CSCLP 04
, 2004
"... Neighborhood Interchangeability (NI) identifies the equivalent values in the domain of a variable of a Constraint Satisfaction Problem (CSP) by considering only the constraints that directly apply to the variable. Freuder described an algorithm for efficiently computing NI values in binary CSPs. In ..."
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Cited by 7 (2 self)
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Neighborhood Interchangeability (NI) identifies the equivalent values in the domain of a variable of a Constraint Satisfaction Problem (CSP) by considering only the constraints that directly apply to the variable. Freuder described an algorithm for efficiently computing NI values in binary CSPs. In this paper, we show that the generalization of this algorithm to nonbinary CSPs is not straightforward, and introduce an efficient algorithm for computing NI values in the presence of nonbinary constraints. Further, we show how to interleave this mechanism with search for solving CSPs, thus yielding a dynamic bundling strategy. While the goal of dynamic bundling is to produce multiple robust solutions, we empirically show that it does not increase (but significantly decreases) the cost of search. 1
On the Dynamic Detection of Interchangeability in Finite Constraint Satisfaction Problems
 In Proceedings of CP2001
, 2001
"... We investigate techniques to discover and exploit problem structure in the form of interchangeability. We enhance the performance of backtrack search with forwardchecking (FCBT) for finding all solutions to a finite Constraint Satisfaction Problem(CSP) with dynamic interchangeability detection ..."
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Cited by 7 (3 self)
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We investigate techniques to discover and exploit problem structure in the form of interchangeability. We enhance the performance of backtrack search with forwardchecking (FCBT) for finding all solutions to a finite Constraint Satisfaction Problem(CSP) with dynamic interchangeability detection and dynamic variable ordering. We evaluate these strategies both theoretically and empirically.
A Method of Program Understanding using Constraint Satisfaction for Software Reverse Engineering
, 1996
"... The process of understanding a source code in a highlevel programming language is a complex cognitive task. The provision of helpful decision aid subsystems would be of great benefit to software maintainers. Given a library of program plan templates, generating a partial understanding of a piece of ..."
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Cited by 5 (2 self)
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The process of understanding a source code in a highlevel programming language is a complex cognitive task. The provision of helpful decision aid subsystems would be of great benefit to software maintainers. Given a library of program plan templates, generating a partial understanding of a piece of software source code can be shown to correspond to the construction of mappings between segments of the source code and particular program plans represented in a library of domain source programs (plans). These mappings can be used as part of the larger task of reverse engineering source code, to facilitate many software engineering tasks such as software reuse, and for program maintenance. We present a novel model of program understanding using constraint satisfaction. The model composes a partial global picture of source program code by transforming knowledge about the problem domain and the program structure into constraints. These constraints facilitate the efficient construction of ma...
Techniques for Bundling the Solution Space of Finite Constraint Satisfaction Problems
, 2001
"... We study the backtracksearch procedure with forward checking (FCBT) for finding all solutions to a finite Constraint Satisfaction Problem (CSP). We describe ..."
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Cited by 4 (4 self)
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We study the backtracksearch procedure with forward checking (FCBT) for finding all solutions to a finite Constraint Satisfaction Problem (CSP). We describe
Backtrackfree search for realtime constraint satisfaction
 In CP, LNCS 3258
, 2004
"... Abstract. A constraint satisfaction problem (CSP) model can be preprocessed to ensure that any choices made will lead to solutions, without the need to backtrack. This can be especially useful in a realtime process control or online interactive context. The conventional machinery for ensuring backt ..."
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Cited by 3 (1 self)
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Abstract. A constraint satisfaction problem (CSP) model can be preprocessed to ensure that any choices made will lead to solutions, without the need to backtrack. This can be especially useful in a realtime process control or online interactive context. The conventional machinery for ensuring backtrackfree search, however, adds additional constraints, which may require an impractical amount of space. A new approach is presented here that achieves a backtrackfree representation by removing values. This may limit the choice of solutions, but we are guaranteed not to eliminate them all. We show that in an interactive context our proposal allows the system designer and the user to collaboratively establish the tradeoff in space complexity, solution loss, and backtracks. 1