Results 1  10
of
324
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 ..."
Abstract

Cited by 469 (21 self)
 Add to MetaCart
(Show Context)
. 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 a maximal number of constraints. Standard backtracking and local consistency techniques for solving constraint satisfaction problems can be adapted to cope with, and take advantage of, the differences between partial and complete constraint satisfaction. Extensive experimentation on maximal satisfaction problems illuminates the relative and absolute effectiveness of these methods. A general model of partial constraint satisfaction is proposed. 1 Introduction Constraint satisfaction involves finding values for problem variables subject to constraints on acceptable combinations of values. Constraint satisfaction has wide application in artificial intelligence, in areas ranging from temporal r...
Adopt: asynchronous distributed constraint optimization with quality guarantees
 ARTIFICIAL INTELLIGENCE LABORATORY, MASSACHUSETTS INSTITUTE OF TECHNOLOGY
, 2005
"... ..."
(Show Context)
SemiringBased Constraint Satisfaction and Optimization
 JOURNAL OF THE ACM
, 1997
"... We introduce a general framework for constraint satisfaction and optimization where classical CSPs, fuzzy CSPs, weighted CSPs, partial constraint satisfaction, and others can be easily cast. The framework is based on a semiring structure, where the set of the semiring specifies the values to be asso ..."
Abstract

Cited by 207 (26 self)
 Add to MetaCart
(Show Context)
We introduce a general framework for constraint satisfaction and optimization where classical CSPs, fuzzy CSPs, weighted CSPs, partial constraint satisfaction, and others can be easily cast. The framework is based on a semiring structure, where the set of the semiring specifies the values to be associated with each tuple of values of the variable domain, and the two semiring operations (1 and 3) model constraint projection and combination respectively. Local consistency algorithms, as usually used for classical CSPs, can be exploited in this general framework as well, provided that certain conditions on the semiring operations are satisfied. We then show how this framework can be used to model both old and new constraint solving and optimization schemes, thus allowing one to both formally justify many informally taken choices in existing schemes, and to prove that local consistency techniques can be used also in newly defined schemes.
An Asynchronous Complete Method for Distributed Constraint Optimization
 In AAMAS
, 2003
"... We present a new polynomialspace algorithm, called Adopt, for distributed constraint optimization (DCOP). DCOP is able to model a large class of collaboration problems in multiagent systems where a solution within given quality parameters must be found. Existing methods for DCOP are not able to pr ..."
Abstract

Cited by 131 (32 self)
 Add to MetaCart
We present a new polynomialspace algorithm, called Adopt, for distributed constraint optimization (DCOP). DCOP is able to model a large class of collaboration problems in multiagent systems where a solution within given quality parameters must be found. Existing methods for DCOP are not able to provide theoretical guarantees on global solution quality while operating both efficiently and asynchronously. Adopt is guaranteed to find an optimal solution, or a solution within a userspecified distance from the optimal, while allowing agents to execute asynchronously and in parallel. Adopt obtains these properties via a distributed search algorithm with several novel characteristics including the ability for each agent to make local decisions based on currently available information and without necessarily having global certainty. Theoretical analysis shows that Adopt provides provable quality guarantees, while experimental results show that Adopt is significanfly more efficient than synchronous methods. The speedups are shown to be partly due to the novel search strategy employed and partly due to the asynchrony of the algorithm.
Semiringbased CSPs and Valued CSPs: Frameworks, Properties, and Comparison
 Constraints
, 1999
"... In this paper we describe and compare two frameworks for constraint solving where classical CSPs, fuzzy CSPs, weighted CSPs, partial constraint satisfaction, and others can be easily cast. One is based on a semiring, and the other one on a totally ordered commutative monoid. While comparing the two ..."
Abstract

Cited by 114 (27 self)
 Add to MetaCart
In this paper we describe and compare two frameworks for constraint solving where classical CSPs, fuzzy CSPs, weighted CSPs, partial constraint satisfaction, and others can be easily cast. One is based on a semiring, and the other one on a totally ordered commutative monoid. While comparing the two approaches, we show how to pass from one to the other one, and we discuss when this is possible. The two frameworks have been independently introduced in [2], [3] and [35].
Arc Consistency for Soft Constraints
 Artificial Intelligence
"... . Traditionally, local consistency is dened as a relaxation of consistency which can be checked in polynomial time. It is accompanied by a corresponding \ltering" or \enforcing" algorithm that computes in polynomial time, and from any given CSP, an equivalent unique CSP which satises t ..."
Abstract

Cited by 91 (26 self)
 Add to MetaCart
(Show Context)
. Traditionally, local consistency is dened as a relaxation of consistency which can be checked in polynomial time. It is accompanied by a corresponding \ltering" or \enforcing" algorithm that computes in polynomial time, and from any given CSP, an equivalent unique CSP which satises the local consistency property. The question whether the notion of local consistency can be extended to soft constraint frameworks has been addressed by several papers, in several settings [4, 14, 12]. The main positive conclusion of these works is that the notion of local consistency can be extended to soft constraints frameworks which rely on an idempotent violation combination operator. However, the question whether this can be done for non idempotent operators as eg, in the MaxCSP problem, is not clear and has lead to several dierent notions of arc consistency [14, 16, 1, 11, 10]. Each of these proposals lacks several of the original properties of local consistency. In this paper, we...
Logical preference representation and combinatorial vote
 ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE
, 2002
"... We introduce the notion of combinatorial vote, where a group of agents (or voters) is supposed to express preferences and come to a common decision concerning a set of nonindependent variables to assign. We study two key issues pertaining to combinatorial vote, namely preference representation and ..."
Abstract

Cited by 90 (16 self)
 Add to MetaCart
We introduce the notion of combinatorial vote, where a group of agents (or voters) is supposed to express preferences and come to a common decision concerning a set of nonindependent variables to assign. We study two key issues pertaining to combinatorial vote, namely preference representation and the automated choice of an optimal decision. For each of these issues, we briefly review the state of the art, we try to define the main problems to be solved and identify their computational complexity.
Existential arc consistency: Getting closer to full arc consistency in weighted csps
 In Proc. of the 19 th IJCAI
, 2005
"... The weighted CSP framework is a soft constraint framework with a wide range of applications. Most current stateoftheart complete solvers can be described as a basic depthfirst branch and bound search that maintain some form of arc consistency during the search. In this paper we introduce a new s ..."
Abstract

Cited by 79 (19 self)
 Add to MetaCart
The weighted CSP framework is a soft constraint framework with a wide range of applications. Most current stateoftheart complete solvers can be described as a basic depthfirst branch and bound search that maintain some form of arc consistency during the search. In this paper we introduce a new stronger form of arc consistency, that we call existential directional arc consistency and we provide an algorithm to enforce it. The efficiency of the algorithm is empirically demonstrated in a variety of domains. 1
Conflictdirected A* and Its Role in Modelbased Embedded Systems
 Journal of Discrete Applied Mathematics
, 2003
"... Artificial intelligence has traditionally used constraint satisfaction and logic to frame a wide range of problems, including planning, diagnosis, cognitive robotics and embedded systems control. However, many decision making problems are now being reframed as optimization problems, involving a sea ..."
Abstract

Cited by 77 (27 self)
 Add to MetaCart
Artificial intelligence has traditionally used constraint satisfaction and logic to frame a wide range of problems, including planning, diagnosis, cognitive robotics and embedded systems control. However, many decision making problems are now being reframed as optimization problems, involving a search over a discrete space for the best solution that satisfies a set of constraints. The best methods for finding optimal solutions, such as A*, explore the space of solutions one state at a time. This paper introduces conflictdirected A*, a method for solving optimal constraint satisfaction problems. Conflictdirected A* searches the state space in best first order, but accelerates the search process by eliminating subspaces around each state that are inconsistent. This elimination process builds upon the concepts of conflict and kernel diagnosis used in modelbased diagnosis[1,2] and in dependencydirected search[36]. Conflictdirected A* is a fundamental tool for building modelbased embedded systems, and has been used to solve a range of problems, including fault isolation[1], diagnosis[7], mode estimation and repair[8], modelcompilation[9] and modelbased programming[10].
Radio Link Frequency Assignment
 Constraints
, 1999
"... The problem of radio frequency assignment is to provide communication channels from limited spectral resources whilst keeping to a minimum the interference suffered by those whishing to communicate in a given radio communication network. This problem is a combinatorial (NPhard) optimization problem ..."
Abstract

Cited by 70 (11 self)
 Add to MetaCart
The problem of radio frequency assignment is to provide communication channels from limited spectral resources whilst keeping to a minimum the interference suffered by those whishing to communicate in a given radio communication network. This problem is a combinatorial (NPhard) optimization problem. In 1993, the CELAR (the French "Centre d'Electronique de l'Armement") built a suite of simplified versions of Radio Link Frequency Assignment Problems (RLFAP) starting from data on a real network (Roisnel 93). Initially designed for assessing the performances of several Constraint Logic Programming languages, these benchmarks have been made available to the public in the framework of the European EUCLID project CALMA (Combinatorial Algorithms for Military Applications).