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The Semantics Of Constraint Logic Programs
 JOURNAL OF LOGIC PROGRAMMING
, 1996
"... This paper presents for the first time the semantic foundations of CLP in a selfcontained and complete package. The main contributions are threefold. First, we extend the original conference paper by presenting definitions and basic semantic constructs from first principles, giving new and comp ..."
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Cited by 872 (14 self)
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This paper presents for the first time the semantic foundations of CLP in a selfcontained and complete package. The main contributions are threefold. First, we extend the original conference paper by presenting definitions and basic semantic constructs from first principles, giving new and complete proofs for the main lemmas. Importantly, we clarify which theorems depend on conditions such as solution compactness, satisfaction completeness and independence of constraints. Second, we generalize the original results to allow for incompleteness of the constraint solver. This is important since almost all CLP systems use an incomplete solver. Third, we give conditions on the (possibly incomplete) solver which ensure that the operational semantics is confluent, that is, has independence of literal scheduling.
Mixed Logical/Linear Programming
 Discrete Applied Mathematics
, 1996
"... Mixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming (MILP). It represents the discrete elements of a problem with logical propositions and provides a more natural modeling framework than MILP. It can also have computational advantages, partly because it elimin ..."
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Cited by 42 (11 self)
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Mixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming (MILP). It represents the discrete elements of a problem with logical propositions and provides a more natural modeling framework than MILP. It can also have computational advantages, partly because it eliminates integer variables when they serve no purpose, provides alternatives to the traditional continuous relaxation, and applies logic processing algorithms. This paper surveys previous work and attempts to organize ideas associated with MLLP, some old and some new, into a coherent framework. It articulates potential advantages and disadvantages of MLLP and illustrates some of them with computational experiments. 1 Introduction Mixed logical/linear programming (MLLP) is a general approach to formulating and solving optimization problems that have both discrete and continuous elements. Mixed integer/linear programming (MILP), the traditional approach, is effective in many instances. But it unn...
Semantics for using Stochastic Constraint Solvers in Constraint Logic Programming
 Journal of Functional and Logic Programming
, 1998
"... This paper proposes a number of models for integrating stochastic constraint solvers into constraint logic programming systems in order to solve constraint satisfaction problems efficiently. Stochastic solvers can solve hard constraint satisfaction problems very efficiently, and constraint logic ..."
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Cited by 4 (1 self)
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This paper proposes a number of models for integrating stochastic constraint solvers into constraint logic programming systems in order to solve constraint satisfaction problems efficiently. Stochastic solvers can solve hard constraint satisfaction problems very efficiently, and constraint logic programming allows heuristics and problem breakdown to be encoded in the same language as the constraints. Hence their combination is attractive. Unfortunately there is a mismatch in the kind of information a stochastic solver provides, and that which a constraint logic programming system requires. We study the semantic properties of the various models of constraint logic programming systems that make use of stochastic solvers, and give soundness and completeness results for their use. We describe an example system we have implemented using a modified neural network simulator, GENET, as a constraint solver. We briefly compare the efficiency of these models against the propagation base...
Constraint Based Reasoning with Constraint Logic Programming and Array Based Logic
, 1996
"... The paper describes how Constraint Based Reasoning (CBR) can be performed with two different paradigms, Constraint Logic Programming (CLP) and Array Based Logic (ABL). The author describes the operation of Constraint Logic Programming emphasizing CLP techniques for finite domain problems such as sea ..."
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The paper describes how Constraint Based Reasoning (CBR) can be performed with two different paradigms, Constraint Logic Programming (CLP) and Array Based Logic (ABL). The author describes the operation of Constraint Logic Programming emphasizing CLP techniques for finite domain problems such as search strategies and consistency techniques. An explanation of Array Based Logic is presented including a description of methods for creating, joining and compressing ABL relations as well as an heuristic for building a system of relations in ABL. A familiar cryptogram is used as an example to demonstrate the operation of the two approaches for finite domain constraint problems. Some potential avenues of research are also presented. 1 Introduction In recent years, there has been a substantial increase in interest in Constraint Based Reasoning (CBR) among computer scientists and engineers. The great potential of CBR as a problem solving tool is becoming increasingly apparent. Known areas of ...
Ph.D. Thesis: TD3/94 Negation and Infinite Computations in Logic Programming
, 1994
"... The other two aspects are tackled within the more general framework of constraint logic programming. This language is reformulated in algebraic terms as the free language generated by a BNF grammar. This allows us to define a structured operational semantics, based on a transition system, by means o ..."
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The other two aspects are tackled within the more general framework of constraint logic programming. This language is reformulated in algebraic terms as the free language generated by a BNF grammar. This allows us to define a structured operational semantics, based on a transition system, by means of which a notion of observables is introduced, also including the results of infinite computations. Then, a compositional semantics based on logical operators is defined, and it is shown its full correspondence with the observables. The denotational meaning of the program is obtained by considering the domain of the upwardclosed Scottcompact sets of constraints (the Smith powerdomain of the domain of constrains). It turns out that the wellknown Negation As Failure of Logic Programming is just the Heyting negation on this domain.