P. Codognet and D. Diaz. Boolean constraint solving using clp(FD). In D. Miller, editor, 1993.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....was first implemented in [14] where finite interval constraints of the form x in r were solved via an extension of the WAM [17] Well known CLP systems such as SICStus [31] and IF Prolog [27] nowintegrate the xinrconstraint to provide a glass box solver for FD, the finite domain of integers. In [12], the idea was extended to the clp(FD B) system. This system integrates a Boolean solver with the existing FD solver. A version of the clp(FD B) called clp(B) developed by Codognet and Diaz [13] solely for the Boolean domain, gave an efficiency that was, on average, an order of magnitude faster ....

P. Codognet and D. Diaz. Boolean constraint solving using clp(FD). In D. Miller, editor, 1993.

....of constraint based programs is hard. Also, one lesson learned from practical applications is that constraints are often heterogeneous and application speci c. Several proposals have been made to allow more exibility and customization of constraint solvers, often termed glass box approaches [36, 98]. The most far reaching proposal is the rule based formalism. In this approach, the constraint propagation is achieved by repeated application of rules. Rule based Constraint Programming Rule based programming began with Arti cial Intelligence rule based systems in the seventies. It is a ....

....that the output Z must be equal to 0. Hence, the goal and(0,Y,Z) will result in Z=0. These rules are the well known rules that can be found in several papers describing the propagation of boolean constraints, e.g. in form of demons [39] conditionals [99] CHR rules [45] or proof systems [36, 21]. Our aim is to provide a method to generate such rules automatically provided the user speci es the right hand side of the rules to be a conjunction of equality constraints. Extension (Chapter 5) The operational semantics of CHR di ers from SLD resolution in various ways. Most of these ....

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P. Codognet and D. Diaz. Boolean constraint solving using clp(FD). In D. Miller, editor, Logic Programming - Proceedings of the 1993.

....of constraint based programs is hard. Also, one lesson learned from practical applications is that constraints are often heterogeneous and application speci c. Several proposals have been made to allow more exibility and customization of constraint solvers, often termed glass box approaches [5,16]. The most far reaching proposal is the no box approach: Constraint Handling Rules (CHR) 7] 3 Java Constraint Handling Rules Constraint Handling Rules (CHR) 7] is a high level language especially designed for writing constraint solvers either from scratch or by modifying existing solvers. ....

....type Object. They are associated with a type and a name. Object X = new Object( cs.addVariable(X, java.lang.Integer , X ) The last step in setting up the constraint system is inserting initial constraints with the addGoalConstraint method of ConstraintSystem. Here, the constraint fdEnu(X,[2,3,4,5,6]) is created and inserted into the constraint store: cs.addGoalConstraint(new FDENUConstraint(X,createList(2,6) Now, the search engine is being set up. In this particular example, the values of the variable X should simply be enumerated. So, a container with the variable is created: ....

P. Codognet and D. Diaz. Boolean constraint solving using clp(FD). In D. Miller, editor, Logic Programming - Proceedings of the 1993.

....scheduling solver using the highly restricted but ecient block mechanism of SICStus, and (SICS v ) where the ground variable numbers in the CHR solver are replaced by Prolog variables, allowing the use of attribute variable indices. The comparison uses ve simple Boolean benchmarks (most from [2]) the rst pigeonn m places n pigeons in m pigeon holes (the 24 24 query succeeds, while 8 7 fails) schurn Schurs s lemma for n (see [2] the 13 query is the largest n that succeeds) queensn the Boolean version of this classic problem; mycien m which colors a 5 colorable graph (taken from ....

....the CHR solver are replaced by Prolog variables, allowing the use of attribute variable indices. The comparison uses ve simple Boolean benchmarks (most from [2] the rst pigeonn m places n pigeons in m pigeon holes (the 24 24 query succeeds, while 8 7 fails) schurn Schurs s lemma for n (see [2]) the 13 query is the largest n that succeeds) queensn the Boolean version of this classic problem; mycien m which colors a 5 colorable graph (taken from [16] with n nodes and m edges with 4 colours; and fulladder which searches for a single faulty gate in a n bit adder (see e.g. 14] for the ....

P. Codognet and D. Diaz. Boolean constraint solving using clp(FD). In Procs. of ILPS'

....over propagation: with Y X we also propagate changes in the lower bound of Y to X, whereas we can avoid this with indexical constraints. A discussion of an implementation of indexical constraints is given in [75] One application of this work is a constraint solver for Boolean constraints [56]; we describe this application in Section 13.5. 9.4. Negation Treatments of negation in logic programming lift readily to constraint logic programming, with only minor adjustments necessary. Indeed many of the semantics for programs with negation are essentially propositional, being based upon ....

....solvers of CHIP, for example, uses variable elimination and these diagrams. A related technique is based on enumeration and propagation. The constraints are expressed as a conjunction of simple constraints and then local propagation simplifies the conjunction after each enumeration step. See [56], for example. The method used in Prolog III [21] is a modification of SL resolution whose main element is the elimination of redundant expressions. Another technique comes from Operations Research. Here the boolean formula is restated in arithmetic form, with variables constrained to be 0 and 1. ....

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P. Codognet & D. Diaz, Boolean Constraint Solving using clp(FD), Proc. International Logic Programming Symposium, 525--539, 1993.

....host langage. Local constraints are an application of hypothetical reasoning. They themselves have as an application the possibility to program labelling in the same model as constraint programming. Imagine for instance a set of CHR rules, clp fd, for handling finite domains in the CLP(FD) style [CD93]. One could write the following program: use clp fd in var X : tell Constraints in (ask min X Mn ask max X Mx Md is (Mn Mx) 2 tell X Md in : tell X Md in : A set of CHR rules is loaded (use) then a set of constraint variables (including X) are introduced, ....

....solvers. Our current prototype implementation is naive in many respects, but we believe that techniques that have been useful for improving original CHR can also be useful in our context. Other techniques such as embedding lists of constraints in variables such as in the in constraints of CLP(FD) [CD93] fits well our representation of constrained variables. Ideally the push and pull semantics could be used for all CHR rules, but in practice, some rules must be used only in one direction. In fact we use a different syntax to recognize these cases, but it would be better to recognize it from ....

P. Codognet and D. Diaz. Boolean constraint solving using clp(fd). In D. Miller, editor, 10th Int. Logic Programming Symp., pages 525--539, 1993.

....the presentation, generally modelled using finite domains or reals as these are the simplest to present in a concise manner. However this should not be taken to imply that no other domains are possible. The literature contains discussion of strings, booleans, and rational and infinite trees [16, 17, 18, 77]. We now present a slightly different domain, based on sets and subsets. This differs from those already seen because the domain is only partially ordered (by subset inclusion) Consider the problem of organising interpreters for a meeting of an international organisation. Let us assume that there ....

Philippe Codognet and Daniel Diaz. Boolean Constraint Solving Using clp(FD). In ILPS'93: Proceedings 3rd International Logic Programming Symposium, pages 525--539, Vancouver, 1993.

....frequent ones in CLP languages. We rapidly review here solvers from other domains that have been implemented in a CLP language: ffl boolean algebra: this domain, which only contains the 2 truth values (true and false) is a special case of finite domain and the previous techniques can be used [CD93] with all their limitations. The usual constraint language is the language of mathematical propositional logic and includes conjunction, disjunction, implication, equivalence. The satisfiability problem is the general sat problem [GJ79] which is again NP complete. A large number of ....

....a large set of 12 For more information, contact Joxan Jaffar via e mail (joxan watson.ibm.com) 13 However, Clp(R) does not include a finite domain solver, one of the main novelty of constraint programming. People interested in finite domains may try to get clp(FD) another free system [CD93] available via anonymous FTP at ftp.inria.fr: INRIA Projects ChLoE LOGIC PROGRAMMING clp fd. primitives is available to express non linear constraints (e.g. Z = X Y, Y = log(X) and the language has been essentially used to deal with partially non linear problems. The system contains ....

P. Codognet and D. Diaz. Boolean constraints solving using clp(fd). In International Logic Programming Symposium, pages 529--539, 1993.

....of the choice point segment the term belongs to (see Section 2.3.1) Trailing is only necessary if the current choice point segment is different from the segment stored in the term. Time stamping is an essential technique for any practical constraint solver. 2.3. 2 clp(FD) The clp(FD) system [29, 40] is a finite domain solver integrated into a WAM emulator. It was built by Daniel Diaz and Philippe Codognet at INRIA (Rocquencourt, France) It uses a glass box approach. Instead of considering a constraint solver as a black box (in the manner of CHIP) a set of primitive operations is added ....

Philippe Codognet and Daniel Diaz. Boolean Constraint Solving using clp(FD). In 10th ILPS, pages 525--539, MIT Press, October 1993.

....not assured and ffl there is no solved form. Obviously, 0 1 constraint satisfaction problems can be easily expressed as finite domain problems by restricting the domain of each domain variable to f0; 1g. Solving 0 1 problems and classical Boolean problems with this approach can be quite efficient [CD93]. Our goal is to provide a complete constraint solver for 0 1 constraints that computes a solved form of the accumulated constraints and provides an easy check of logical entailment and therefore satisfiability. Especially for concurrent constraint programming languages [SR90] deciding logical ....

P. Codognet and D. Diaz. Boolean constraint solving using clp(FD). In D. Miller, editor, Logic Programming. Proceedings of the 1993 international symposium, 1993.

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P. Codognet and D. Diaz. Boolean Constraint Solving Using clp(FD). In International Logic Programming Symposium, Vancouver, British Columbia, Canada, MIT Press 1993.

.... hardware circuit veri cation, and many boolean solvers have been developed, which are based on very di erent methods, such as SLresolution, Davis Putman like enumeration algorithms, BDD based methods, Operational Research based approaches and more recently based on local propagation schemes, see [12] or [14] for a general review. It is also worth distinguishing between stand alone solvers intended to take a set of boolean formulas as input, and CLP languages that o er much more exibility by providing a full logic language to state the problem and generate the boolean formulas. Only ....

....logic language to state the problem and generate the boolean formulas. Only PrologIII, CHIP and clp(B FD) fall in the latter category. As we will see later, clp(B FD) is more ecient than CHIP and, surprizingly, it is also more ecient (several times faster) than such special purpose solvers (see [12] or [14] for a comprehensive comparision) 7.2. Boolean Constraints A boolean constraint on a set V of variables is one of the following formulas: and(X; Y; Z) or(X; Y; Z) not(X; Y ) X = Y , for X;Y; Z 2 V . The intuitive meaning of these constraints is: X Y Z, X Y Z, X :Y , and X ....

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P. Codognet and D. Diaz. Boolean Constraint Solving Using clp(FD). In International Logic Programming Symposium, Vancouver, British Columbia, Canada, MIT Press, 1993.

.... hardware circuit verification, and many boolean solvers have been developed, which are based on very different methods, such as SLresolution, Davis Putman like enumeration algorithms, BDD based methods, Operational Research based approaches and more recently based on local propagation schemes, see [12] or [14] for a general review. It is also worth distinguishing between stand alone solvers intended to take a set of boolean formulas as input, and CLP languages that offer much more flexibility by providing a full logic language to state the problem and generate the boolean formulas. Only ....

....language to state the problem and generate the boolean formulas. Only PrologIII, CHIP and clp(B FD) fall in the latter category. As we will see later, clp(B FD) is more efficient than CHIP and, surprizingly, it is also more efficient (several times faster) than such special purpose solvers (see [12] or [14] for a comprehensive comparision) 7.2. Boolean Constraints A boolean constraint on a set V of variables is one of the following formulas: and(X; Y; Z) or(X; Y; Z) not(X; Y ) X = Y , for X;Y; Z 2 V . The intuitive meaning of these constraints is: X Y j Z, X Y j Z, X j :Y , and X j Y ....

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P. Codognet and D. Diaz. Boolean Constraint Solving Using clp(FD). In International Logic Programming Symposium, Vancouver, British Columbia, Canada, MIT Press, 1993.

.... correspondance between old (i.e. wamcc) names and new ones (i.e. clp(FD) Executable wamcc names clp(FD) names Prolog compiler wamcc clp fd Gcc compiler w gcc fd gcc Build Makefile bmf wamcc bmf clp fd Library libwamcc.a libclp fd.a Profile library libwamcc pp.a libclp fd pp.a Some papers [2, 3, 4, 5, 6, 7] presents clp(FD) and its extensions. Basically, clp(FD) deals with only one basic constraint X in r (see section 3.1) X is a finite domain variable and r denotes a range, which can be not only a constant range, e.g. 1: 10 but also an indexical range using: ffl min(Y ) which represents the ....

P. Codognet and D. Diaz. Boolean Constraint Solving Using clp(FD). In International Logic Programming Symposium, Vancouver, British Columbia, Canada, MIT Press 1993.

....better than the original boolean unification algorithm for nearly all problems and is competitive with special purpose boolean solvers. A similar approach has been used to define clp(B FD) where boolean constraint solving is performed on top of the finite domain constraint solver of clp(FD) [4]. Indeed, the boolean constraints are encoded thanks to the low level X in r primitive of clp(FD) This idea of compiling complex constraints into simpler low level constraints has been originally proposed for finite domain constraints by [20] and called the glass box approach. The clp(B FD) ....

....to take a set of boolean formulas as input while only clp(B FD) and CHIP provide boolean solvers integrated into full CLP languages, offering therefore more flexibility. These solvers are described in more details in [6] clp(B FD) is a CLP language on booleans built on the top of clp(FD) [4]. Times for clp(B FD) were also measured on a Sun Sparc 2. Exactly the same programs were run on both systems. CHIP is also a CLP language (and not only a constraint solver) and thus accepts the same programs as clp(B) Moreover, it also uses a boolean constraint solver based on finite domains ....

P. Codognet and D. Diaz. Boolean Constraint Solving Using clp(FD). In International Logic Programming Symposium, Vancouver, British Columbia, Canada, MIT Press 1993.

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P. Codognet and D. Diaz. Boolean constraint solving using clp(FD). In D. Miller, editor, 1993.

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P. Codognet and D. Diaz. Boolean constraint solving using clp(FD). In Procs. of ILPS'1993.

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P. Codognet and D. Diaz. Boolean constraint solving using clp(FD). In Procs. of ILPS'1993.

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