1,284 research outputs found
Finite domain constraint programming systems
Tutorial at CP'2002, Principles and Practice of Constraint Programming. Powerpoint slides.</p
Improving PARMA Trailing
Taylor introduced a variable binding scheme for logic variables in his PARMA
system, that uses cycles of bindings rather than the linear chains of bindings
used in the standard WAM representation. Both the HAL and dProlog languages
make use of the PARMA representation in their Herbrand constraint solvers.
Unfortunately, PARMA's trailing scheme is considerably more expensive in both
time and space consumption. The aim of this paper is to present several
techniques that lower the cost.
First, we introduce a trailing analysis for HAL using the classic PARMA
trailing scheme that detects and eliminates unnecessary trailings. The
analysis, whose accuracy comes from HAL's determinism and mode declarations,
has been integrated in the HAL compiler and is shown to produce space
improvements as well as speed improvements. Second, we explain how to modify
the classic PARMA trailing scheme to halve its trailing cost. This technique is
illustrated and evaluated both in the context of dProlog and HAL. Finally, we
explain the modifications needed by the trailing analysis in order to be
combined with our modified PARMA trailing scheme. Empirical evidence shows that
the combination is more effective than any of the techniques when used in
isolation.
To appear in Theory and Practice of Logic Programming.Comment: 36 pages, 7 figures, 8 table
Exploring Alternative Restoration Techniques in Constraint Programming
Master'sMASTER OF SCIENC
Incremental copying garbage collection for WAM-based Prolog systems
The design and implementation of an incremental copying heap garbage
collector for WAM-based Prolog systems is presented. Its heap layout consists
of a number of equal-sized blocks. Other changes to the standard WAM allow
these blocks to be garbage collected independently. The independent collection
of heap blocks forms the basis of an incremental collecting algorithm which
employs copying without marking (contrary to the more frequently used mark©
or mark&slide algorithms in the context of Prolog). Compared to standard
semi-space copying collectors, this approach to heap garbage collection lowers
in many cases the memory usage and reduces pause times. The algorithm also
allows for a wide variety of garbage collection policies including generational
ones. The algorithm is implemented and evaluated in the context of hProlog.Comment: 33 pages, 22 figures, 5 tables. To appear in Theory and Practice of
Logic Programming (TPLP
Logic programming in the context of multiparadigm programming: the Oz experience
Oz is a multiparadigm language that supports logic programming as one of its
major paradigms. A multiparadigm language is designed to support different
programming paradigms (logic, functional, constraint, object-oriented,
sequential, concurrent, etc.) with equal ease. This article has two goals: to
give a tutorial of logic programming in Oz and to show how logic programming
fits naturally into the wider context of multiparadigm programming. Our
experience shows that there are two classes of problems, which we call
algorithmic and search problems, for which logic programming can help formulate
practical solutions. Algorithmic problems have known efficient algorithms.
Search problems do not have known efficient algorithms but can be solved with
search. The Oz support for logic programming targets these two problem classes
specifically, using the concepts needed for each. This is in contrast to the
Prolog approach, which targets both classes with one set of concepts, which
results in less than optimal support for each class. To explain the essential
difference between algorithmic and search programs, we define the Oz execution
model. This model subsumes both concurrent logic programming
(committed-choice-style) and search-based logic programming (Prolog-style).
Instead of Horn clause syntax, Oz has a simple, fully compositional,
higher-order syntax that accommodates the abilities of the language. We
conclude with lessons learned from this work, a brief history of Oz, and many
entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic
Programming
Modern techniques for constraint solving the CASPER experience
Dissertação apresentada para obtenção do
Grau de Doutor em Engenharia Informática,
pela Universidade Nova de Lisboa, Faculdade
de Ciências e TecnologiaConstraint programming is a well known paradigm for addressing combinatorial problems which has enjoyed considerable success for solving many relevant industrial and academic problems. At the heart of constraint programming lies the constraint solver, a computer program which attempts to find a solution to the problem, i.e. an assignment of all the variables in the problemsuch that all the constraints are satisfied.
This dissertation describes a set of techniques to be used in the implementation of a constraint solver. These techniques aim at making a constraint solver more extensible and efficient,two properties which are hard to integrate in general, and in particular within a constraint solver. Specifically, this dissertation addresses two major problems: generic incremental
propagation and propagation of arbitrary decomposable constraints. For both problemswe
present a set of techniques which are novel, correct, and directly concerned with extensibility and efficiency.
All the material in this dissertation emerged from our work in designing and implementing a generic constraint solver. The CASPER (Constraint Solving Platformfor Engineering and Research)solver does not only act as a proof-of-concept for the presented techniques, but also served as the common test platform for the many discussed theoretical models. Besides the work related to the design and implementation of a constraint solver, this dissertation also
presents the first successful application of the resulting platform for addressing an open research problem, namely finding good heuristics for efficiently directing search towards a solution
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