Fundamental properties of networks of constraints: A new formulation

Networks of constraints are a simple knowledge representation model, useful for describing large classes of problems in picture recognition and scene analysis, in the representation of physical systems and in the specification of software systems. Nodes in the network represent variables to be assigned, while arcs are constraints to be satisfied by the adjacent variables; constraints are simply seen as relation specifying the acceptable tuples of values of the variables. Solutions of the network are variable assignments which simultaneously satisfy all constraints.

[1]  Michael J. Quinn,et al.  Taking Advantage of Stable Sets of Variables in Constraint Satisfaction Problems , 1985, IJCAI.

[2]  Robert Balzer,et al.  Operational specification as the basis for rapid prototyping , 1982 .

[3]  R M Haralick,et al.  The consistent labeling problem: part I. , 1979, IEEE transactions on pattern analysis and machine intelligence.

[4]  James Arthur Gosling,et al.  Algebraic constraints , 1983 .

[5]  Ugo Montanari,et al.  Networks of constraints: Fundamental properties and applications to picture processing , 1974, Inf. Sci..

[6]  Jeffrey D. Ullman,et al.  Parallel complexity of logical query programs , 1986, 27th Annual Symposium on Foundations of Computer Science (sfcs 1986).

[7]  Francesca Rossi,et al.  An Efficient Algorithm for the Solution of Hierarchical Networks of Constraints , 1986, Graph-Grammars and Their Application to Computer Science.

[8]  Eugene C. Freuder.  Synthesizing constraint expressions , 1978, CACM.

[9]  David L. Waltz,et al.  Generating Semantic Descriptions From Drawings of Scenes With Shadows , 1972 .

[10]  Eugene C. Freuder.  A Sufficient Condition for Backtrack-Free Search , 1982, JACM.

[11]  Johan de Kleer,et al.  A Qualitative Physics Based on Confluences , 1984, Artif. Intell..

[12]  Eugene C. Freuder,et al.  The Complexity of Some Polynomial Network Consistency Algorithms for Constraint Satisfaction Problems , 1985, Artif. Intell..

[13]  Rina Dechter,et al.  Network-Based Heuristics for Constraint-Satisfaction Problems , 1987, Artif. Intell..

[14]  Johan de Kleer,et al.  How Circuits Work , 1984, Artif. Intell..

[15]  David L. Waltz,et al.  Understanding Line drawings of Scenes with Shadows , 1975 .

[16]  Azriel Rosenfeld,et al.  Scene Labeling by Relaxation Operations , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[17]  Alan K. Mackworth.  Consistency in Networks of Relations , 1977, Artif. Intell..

[18]  Benjamin Kuipers,et al.  Commonsense Reasoning about Causality: Deriving Behavior from Structure , 1984, Artif. Intell..

[19]  Azriel Rosenfeld,et al.  Reduction operations for constraint satisfaction , 1978, Inf. Sci..

[20]  Robert M. Haralick,et al.  Increasing Tree Search Efficiency for Constraint Satisfaction Problems , 1979, Artif. Intell..

[21]  Robert Balzer,et al.  A 15 Year Perspective on Automatic Programming , 1985, IEEE Transactions on Software Engineering.

[22]  Guy L. Steele,et al.  The definition and implementation of a computer programming language based on constraints , 1980 .

[23]  Raimund Seidel,et al.  A New Method for Solving Constraint Satisfaction Problems , 1981, IJCAI.

[24]  Daniel G. Bobrow,et al.  Qualitative Reasoning about Physical Systems: An Introduction , 1984, Artif. Intell..