The phase transition in binary constraint satisfaction problems, i.e. the transition from a region in which almost all problems have many solutions to a region in which almost all problems have no solutions, as the constraints become tighter, is investigated by examining the behaviour of samples of randomly-generated problems. In contrast to theoretical work, which is concerned with the asympto...

Generating technical exercises for various levels of playing ability is important for any instrument method book. Writing exercises by hand can be quite tedious, and severely limits the number of exercises which could be created. This is particularly apparent when we consider computer music tutoring systems, which could benefit from a library of thousands of exercises. This library could be use...

Local consistency techniques such as k-consistency are a key component of specialised solvers for constraint satisfaction problems. In this paper we show that the power of using k-consistency techniques on a constraint satisfaction problem is precisely captured by using a particular inference rule, which we call negative-hyper-resolution, on the standard direct encoding of the problem into Bool...

In Constraint Programming (CP), a portfolio solver uses a variety of different solvers for solving a given Constraint Satisfaction / Optimization Problem. In this paper we introduce sunny-cp2: the first parallel CP portfolio solver that enables a dynamic, cooperative, and simultaneous execution of its solvers in a multicore setting. It incorporates state-of-the-art solvers, providing also a usa...

The semiring-based constraint satisfaction problems (semiring CSPs), proposed by Bistarelli, Montanari and Rossi [3], is a very general framework of soft constraints. In this paper we propose an abstraction scheme for soft constraints that uses semiring homomorphism. To find optimal solutions of the concrete problem, the idea is, first working in the abstract problem and finding its optimal sol...

We propose to integrate ACO in a Constraint Programming (CP) language. Basically, we use the CP language to describe the problem to solve by means of constraints and we use the CP propagation engine to reduce the search space and check constraint satisfaction; however, the classical backtrack search of CP is replaced by an ACO search. We report first experimental results on the car sequencing p...

We give a survey of recent results on the complexity of constraint satisfaction problems. Our main emphasis is on tractable structural restrictions.

In this paper we describe an approach for integrating CR-Prolog and constraint programming, in which CR-Prolog is viewed as a specification language for constraint satisfaction problems. Differently from other methods of integrating ASP and constraint programming, our approach has the advantage of allowing the use of off-the-shelf, unmodified ASP solvers and constraint solvers, and of global co...

Constraint Satisfaction Problems typically exhibit strong combinatorial explosion. In this paper we present some models and techniques aimed at improving efficiency in Constraint Logic Programming. A hypergraph model of constraints is presented and an outline of strategy planning approach focused on entropy minimization is put forward. An example cryptoaritmetic problem is explored in order to ...