Showing papers in "Constraints - An International Journal in 2001"

Random Constraint Satisfaction: Flaws and Structure

Abstract: A recent theoretical result by Achlioptas et al. shows that many models of random binary constraint satisfaction problems become trivially insoluble as problem size increases. This insolubility is partly due to the presence of ‘flawed variables,’ variables whose values are all ‘flawed’ (or unsupported). In this paper, we analyse how seriously existing work has been affected. We survey the literature to identify experimental studies that use models and parameters that may have been affected by flaws. We then estimate theoretically and measure experimentally the size at which flawed variables can be expected to occur. To eliminate flawed values and variables in the models currently used, we introduce a ‘flawless’ generator which puts a limited amount of structure into the conflict matrix. We prove that such flawless problems are not trivially insoluble for constraint tightnesses up to 1/2. We also prove that the standard models B and C do not suffer from flaws when the constraint tightness is less than the reciprocal of domain size. We consider introducing types of structure into the constraint graph which are rare in random graphs and present experimental results with such structured graphs.

Musical Harmonization with Constraints: A Survey

Abstract: We survey works on the musical problem of automatic harmonization. This problem, which consists in creating musical scores which satisfy given rules of harmony, has been the object of numerous studies, most of them using constraint techniques in one way or another. We outline the main results obtained and the current status of this category of problems.

Random Constraint Satisfaction: A More Accurate Picture

Abstract: In the last few years there has been a great amount of interest in Random Constraint Satisfaction Problems, both from an experimental and a theoretical point of view. Quite intriguingly, experimental results with various models for generating random CSP instances suggest that the probability of such problems having a solution exhibits a “threshold-like” behavior. In this spirit, some preliminary theoretical work has been done in analyzing these models asymptotically, i.e., as the number of variables grows. In this paper we prove that, contrary to beliefs based on experimental evidence, the models commonly used for generating random CSP instances i>do not have an asymptotic threshold. In particular, we prove that asymptotically i>almost all instances they generate are overconstrained, suffering from trivial, local inconsistencies. To complement this result we present an alternative, single-parameter model for generating random CSP instances and prove that, unlike current models, it exhibits non-trivial asymptotic behavior. Moreover, for this new model we derive explicit bounds for the narrow region within which the probability of having a solution changes dramatically.

The Protein Structure Prediction Problem: A Constraint Optimization Approach using a New Lower Bound

Abstract: The protein structure prediction problem is one of the most (if not i>the most) important problem in computational biology. This problem consists of finding the conformation of a protein with minimal energy. Because of the complexity of this problem, simplified models like Dill's HP-lattice model l15r, l16r have become a major tool for investigating general properties of protein folding. Even for this simplified model, the structure prediction problem has been shown to be NP-complete l5r, l7r. We describe a constraint formulation of the HP-model structure prediction problem, and present the basic constraints and search strategy. Of course, the simple formulation would not lead to an efficient algorithm. We therefore describe redundant constraints to prune the search tree. Furthermore, we need bounding function for the energy of an HP-protein. We introduce a new lower bound based on partial knowledge about the final conformation (namely the distribution of H-monomers to layers).

A Context for Constraint Satisfaction Problem Formulation Selection

Abstract: Much research effort has been applied to finding effective ways for solving constraint satisfaction problems However, the most fundamental aspect of constraint satisfaction problem solving, problem formulation, has received much less attention This is important because the selection of an appropriate formulation can have dramatic effects on the efficiency of any constraint satisfaction problem solving algorithm In this paper, we address the issue of problem formulation We identify the heuristic nature of generating a good formulation and we propose a context for this process Our work presents the research community with a focus for the many elements which affect problem formulation and this is illustrated with the example adding redundant constraints It also provides a significant step towards the goal of automatic selection of problem formulations

Keep-Best Reproduction: A Local Family Competition Selection Strategy and the Environment it Flourishes in

Abstract: This paper presents a comparison of two genetic algorithms (GAs) for constrained ordering problems. The first GA uses the standard selection strategy of roulette wheel selection and generational replacement (STDS), while the second GA uses an intermediate selection strategy in addition to STDS. This intermediate selection strategy keeps only the superior offspring and replaces the inferior offspring with the superior parent. We call this selection strategy i>Keep-Best Reproduction (KBR). The effect of recombination alone, mutation alone and both together are studied. We compare the performance of the different selection strategies and discuss the environment that each selection strategy needs to flourish in. Overall, KBR is found to be the selection strategy of choice. We also present empirical evidence that suggests that KBR is more robust than STDS with regard to operator probabilities and works well with smaller population sizes.

Integrating Constraints and Concurrent Objects in MusicalApplications: A Calculus and its Visual Language

Abstract: We propose { PiCO}, a calculus integrating concurrent objects and constraints, as a base for music composition tools. In contrast with calculi such as NiehrenMueller:Free, milner.parrow.ea:calculus-mobile or TyCO vasconcelos:typed-concurrent, both constraints and objects are primitive notions in { PiCO}. In { PiCO} a base object model is extended with constraints by orthogonally adding the notion of constraint system found in the \rho-calculus OzCalculus. Concurrent processes make use of a constraint store to synchronize communications either via the ask and tell operations of the constraint model or the standard message-passing mechanism of the object model. A message delegation mechanism built into the calculus allows encoding of general forms of inheritance. This paper includes encodings in { PiCO} of the concepts of class and sub-class. These allow us to represent complex partially defined objects such as musical structures in a compact way. We illustrate the transparent interaction of constraints and objects by a musical example involving harmonic and temporal relations. The relationship between Cordial, a visual language for music composition applications, and its underlying model { PiCO} is described.

Guided Genetic Algorithm and its Application to Radio Link Frequency Assignment Problems

Abstract: The Guided Genetic Algorithm (GCA) is a hybrid of Genetic Algorithm and Guided Local Search, a meta-heuristic search algorithm As the search progresses, GGA modifies both the fitness function and fitness template of candidate solutions based on feedback from constraints The fitness template is then used to bias crossover and mutation The Radio Link Frequency Assignment Problem (RLFAP) is a class of problem that has practical relevance to both military and civil applications In this paper, we show how GGA can be applied to the RLFAP We focus on an abstraction of a real life military application that involves the assigning of frequencies to radio links GGA was tested on a set of eleven benchmark problems provided by the French military This set of problems has been studied intensively by a number of prominent groups in Europe It covers a variety of needs in military applications, including the satisfaction of constraints, finding optimal solutions that satisfy all the constraints and optimization of some objective functions whenever no solution exist (“partial constraint satisfaction”) Not only do these benchmark problems vary in problem nature, they are reasonably large for military applications (up to 916 variables, and up to 5548 constraints) This makes them a serious challenge to the generality, reliability as well as efficiency of algorithms We show in this paper that GGA is capable of producing excellent results reliably in the whole set of benchmark problems

A Constraint Based Structure Description Language for Biosequences

Abstract: We report an investigation into how constraint solving techniques can be used to search for patterns in sequences (or strings) of symbols over a finite alphabet. We define a constraint-based structure description language for biosequences, and give the definition of an algorithm to solve the structure searching problem as a CSP. The methodology which we have developed is able to describe two-dimensional structure of biosequences, such as tandem repeats, stem loops, palindromes and pseudo-knots. We also report on an implementation of the language in the constraint logic programming language clp(FD), with test results of a simple searching algorithm, and results from a preliminary implementation in C++ using consistency checking techniques from solving CSP.

Constraint-Based Facial Animation

Abstract: Constraints have been traditionally used for computer animation applications to define side conditions for generating synthesized motion according to a standard, usually physically realistic, set of motion equations. The case of facial animation is very different, as no set of motion equations for facial expressions is available. In this paper we discuss a facial animation editor, which uses numerical constraints for two roles: to declare the mimic repertoire of synthetic faces and other requirements a facial animation has to meet, and to aid the animator in the process of composing a specific animation fulfilling the requirements. The editor is thus also a ``motion sculpturing'' tool, which lifts the task of creating facial animation from the control data manipulation level to the conceptual design level. The major aid of the editor is to repair inconsistencies due to changes made by the user, and revise changes for which no good repair is possible. Also, reuse of constrained animations, especially expressions, is supported. The main machinery behind these services is interval propagation, which, if using certain type of linear inequalities to express the character- as well as the animation-specific requirements, can produce quickly the interval of feasible values for each control variable. If a solution (usually, repair) has to be produced, it is generated by selecting the best one from a restricted set of acceptable solutions, based on user-defined or automatically generated criteria for the choices.

Constraint Techniques for Authoring Multimedia Documents

Abstract: Authoring a multimedia document requires to specify both its spatial layout and its temporal organization, i.e. when and where objects such as pictures, texts and videos appear /disappear on /from the screen and when objects such as audios and videos start /end to play. In this paper, we present some benefits authors can gain when using an authoring tool in which constraints are used to specify these two kinds of information. We describe our experience in building Madeus, a constraint-based environment to design multimedia documents and we point out technical problems that still need to be solved to more completely satisfy author requirements.

Bioinformatics and Constraints

Abstract: This article introduces the topic of bioinformatics to an audience of computer scientists. We discuss the definition of bioinformatics, give a classification of the problem areas which bioinformatics addresses, and illustrate these in detail with examples. We highlight those areas which we believe to be suitable for the application of constraint solving techniques, or where similar techniques are already used. Finally, we give some advice for computer scientists who are considering getting involved in bioinformatics, and provide a resource list and a reading list.

Modelling Musical Structures

Abstract: Modelling musical structures is a research field prominent among mathematicians and computer scientists as well as musicologists, psychomusicologists and musicians. Constraint programming has been proved to be a highly appropriate technique in this field. For the task of automated music composition, in particular, constraints have been shown to describe composition principles in a declarative, natural, and, above all, efficient way since music composition knowledge is in fact a collection of conditions rather than a sort of cookery-book. Unfortunately, many approaches stress the technical aspects of applying constraints and do not think about the concrete role of constraints, i.e. about what music really should be. In general, the composer as an artist is more concerned about what he wants to say through his music than with theoretically (or socially or psychologically) established rules. This means that automated music composition needs practical goals in order to make sense. The role of those goals as well as musical constraints and constraint technologies that help to realize the goals are to be shown in this article. As a modelling example the system COPPELIA is introduced. It generates music on the basis of the structures, goals, and contents of given multimedia presentations. In this relatively young field of constraint application that does not supply such ideal, well-defined and closed sets of conditions as technical applications do, we find it very important to also present general thoughts about the sense of our application, about the development of composition constraints and the conditions under which these constraints work effectively.

Parametric Sequence Alignment with Constraints

Abstract: Approximate matching techniques based on string alignment are important tools for investigating similarities between strings, such as those representing DNA and protein sequences We propose a constraint based approach for parametric sequence alignment which allows for more general string alignment queries where the alignment cost can itself be parameterized as a query with some initial constraints Thus, the costs need not be fixed in a parametric alignment query unlike the case in normal alignment The basic dynamic programming string edit distance algorithm is generalized to a naive algorithm which uses inequalities to represent the alignment score The naive algorithm is rather costly and the remainder of the paper develops an improvement which prunes alternatives where it can and approximates the alternatives otherwise This reduces the number of inequalities significantly and strengthens the constraint representation with equalities We present some preliminary results using parametric alignment on some general alignment queries

RNA Secondary Structure Determination and Representation Based on Constraints Satisfaction

Abstract: A characteristic common to several problems of molecular biology consists in the satisfaction of a set of constraints coming from different sources of biological knowledge. In this paper, we present two problems that take advantage of a constraint satisfaction formulation. The first problem deals with the representation and visualization of RNA secondary structures. The program RNASEARCH implements an original backtracking based algorithm that evaluates at each node the satisfaction of spatial constraints with the aim at drawing a representation without overlap between secondary structural elements. The second problem addresses the determination of RNA secondary structure in accordance with data. With the program SAPSSARN, the application of classic filtering algorithm is used and we discuss a new search algorithm which computes only so called saturated secondary structures. The main result certainly is the possibility to relax the constraint of the absence of secondary structural elements forbidden in secondary structures computed with dynamic programming based approaches: pseudoknots. Finally, we show how each program takes advantage from the other through a protocol driven by constraints.

A Constraint-Based Approach for Deriving 3-D Structures of Cyclic Polypeptides

Abstract: This paper presents an hybrid algorithm for deriving 3-D structures of cyclic polypeptides. The algorithm combines constraint-based techniques with the most widely used methods for non-cyclic polypeptides. The empirical results demonstrate that the proposed hybrid algorithm outperforms traditional methods especially with respect to running times.