J-L. Lauriere. A language and a program for stating and solving combinatorial problems. Arti cial Intelligence, 10:29-127, 1978. Home/Search Document Not in Database Summary Related Articles Check |
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New structures of symbolic constraint objects: sets and graphs.. - Gervet (1993) (2 citations) (Correct)
....constraint such as the bijection (BIJ in ALICE) gives birth to P j2J x ij = 1, conditions on boolean variables x ij . A single image for each element belonging to I means that only one x ij is set to 1. This representation enforcement is very costly as soon as the number of variables increases [2]. Our representation, on the contrary, uses only two variables in each constraint: card(successor(j) 1. 3 The semantic aspect Let us now describe what are the theorical foundations of set and graph constraints. The principal idea is the one of invariant handling. A set or a graph object variable ....
J. L. Lauri`ere. A language and a program for stating and solving combinatorial problems. Artificial Intelligence, 10:29--127, 1978.
Conjunto: Constraint Logic Programming with Finite Set Domains - Gervet (1994) (33 citations) (Correct)
....But from our experiment set constraints are not expressive enough to tackle the problems on graphs. In fact, our objectives are not limited to the definition of set domains but also aim at describing relations in the same way. Lauri ere first addressed this issue in his seminal language ALICE [12]. In Conjunto, a finite relation domain constrains a relation variable R S 1 Theta S 2 where S 1 and S 2 are respectively the domain and the range of R (ground sets) A graph is a specific relation where the domain and range coincide. A forthcoming report will describe this extension to ....
J. L. Lauri`ere. A Language and a Program for Stating and Solving Combinatorial Problems. Artificial Intelligence, 10:29--127, 1978.
Set and Binary Relation Variables Viewed as Constrained Objects.. - Gervet (1993) (3 citations) (Correct)
....Computer Industry Research Centre Arabellastr. 17, D 8000 Munich 81, Germany email: carmen ecrc.de Introduction Sets, relations and graphs are natural notions in Operations Research (OR) In his seminal work, J. L. Lauri ere introduced, sets, relations and graphs as the basic foundations of ALICE [8].These symbolic structures are powerful tools for solving specific OR problems but they are ad hoc. He defined binary relations between sequences and dealt little with set operators themselves. A semantics for sets was introduced in Logic Programming (LP) Languages (finite sets and maps in SETL ....
J. L. Lauri`ere. A Language and a Program for Stating and Solving Combinatorial Problems. Artificial Intelligence, 10:29--127, 1978.
Combining Formal Reasoning Techniques with CSP - Liret, Roy, Pachet (1997) (Correct)
....of formal reasoning on constraints, with classical enumeration techniques. This idea is not new and was the core of the Alice system [9] Alice proposed a scheme for combining formal reasoning and constraint satisfaction to solve combinatorial problems. Alice was validated on several examples [10], and shown to be sometimes more efficient than specialized procedures. However, the Alice experience was difficult to share, because Alice was basically a black box. The performance relied on a judicious choice of complex heuristics ; too few information was accessible about the resolution ....
J.L. Lauri`ere. A Language and a Program for Stating and Solving Combinatorial Problems Artificial Intelligence. Artificial Intelligence, vol. 10, pp. 29-127, 1978.
The Framework Approach for Constraint Satisfaction - Roy, Liret, Pachet (2000) (Correct)
....approach compared to the other ones. Keywords: Constraint satisfaction, Object oriented programming, Frameworks 1 Introduction Constraint satisfaction programming (CSP) is a powerful paradigm for solving combinatorial problems, which was initially seen as an algorithmic issue [Mackworth 1977] [Lauri re 1978]. The first proposals for integrating constraints in a language were developed within the community of logic programming. Constraint logic programming (CLP) was primarily designed to deal with specific computation domains like integer numbers. Its best known representatives are PROLOG III ....
J.-L. Laurière, "A Language and a Program for Stating and Solving Combinatorial Problems" Artificial intelligence, vol. 10(1), pp. 29-127, 1978.
Survey: Practical Applications of Constraint Programming - Wallace (1995) (3 citations) (Correct)
....the current success of constraint technology, and, by showing its benefits, to add to that success. In 1963 Sutherland introduced the Sketchpad system [118] a constraint language for graphical interaction. Other early constraint programming languages were Fikes Ref Arf [44] Lauriere s Alice [78], Sussmann s CONSTRAINTS [116] and Borning s ThingLab [10] These languages already offered the most important features of constraint programming: ffl declarative problem modelling ffl propagation of the effects of decisions ffl efficient search for feasible solutions Each of these three ....
J-L. Lauri`ere. A language and a program for stating and solving combinatorial problems. Artificial Intelligence, 10:29--127, 1978.
Bounds Consistency Techniques for Long Linear Constraints - Harvey, Schimpf (Correct)
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J-L. Lauriere. A language and a program for stating and solving combinatorial problems. Arti cial Intelligence, 10:29-127, 1978.
Reifying Constraint Satisfaction in Smalltalk - Roy, Pachet (1997) (4 citations) (Correct)
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Laurière, J.L. (1978) A Language and a Program for stating and solving combinatorial problems. Artificial Intelligence, Vol. 10, n. 1, pp. 29-127.
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