Introduction A finite domain constraint system can be viewed as an linear integer constraint system in which each variable has an upper and lower bound. Finite domains have been used successfully in Constraint Logic Programming (CLP) languages, for example CHIP [4], to attack combinatorial

We describe the design and implementation of a finite domain constraint solver embedded in a Prolog system using an extended unification mechanism via attributed variables as a generic constraint interface. The solver is essentially a scheduler for indexicals, i.e. reactive functional rules

Using a glass-box theory of finite domain constraints, FD, we show how the entailment of user-defined constraints can be expressed by anti-monotone FD constraints. We also provide an algorithm for checking the entailment and consistency of FD constraints. FD is shown to be expressive enough

Mixture sets were introduced by Herstein and Milnor (1953) to prove a generalised expected utility theorem. Mixture sets provide an axiomatisation of convexity suitable for discrete, as well as continuous, environments (Mongin, 2001). However, the nature of mixture sets over finite domains has been

Abstract. We explore the problem of enciphering members of a finite set M where k = |M | is arbitrary (in particular, it need not be a power of two). We want to achieve this goal starting from a block cipher (which requires a message space of size N =2 n, for some n). We look at a few solutions

In many mathematical models for pattern formation, a regular hexagonal pattern is stable in an infinite region. However, laboratory and numerical experiments are carried out in finite domains, and this imposes certain constraints on the possible patterns. In finite rectangular domains, it is shown

, express 9~y C(~x; ~ y) in the simplest form. [13] showed how a set of constraints over the real domain can be simplified. We present here how we can simplify a set of constraints over finite domains. First, we start by a bref sight on the simplification of the constraints over real domain, then we show

: Carlson, B., 1995. Compiling and Executing Finite Domain Constraints. 175 pp. Uppsala Theses in Computing Science 21, ISSN 0283-359X, ISBN 91-506-1100-3. SICS Dissertation Series 18, ISSN 1101-1335, ISRN SICSD --18--SE. Finite domain constraints are used for specifying and solving complex

In this paper, we bring techniques from operations research to bear on the problem of choosing optimal actions in partially observable stochastic domains. We begin by introducing the theory of Markov decision processes (mdps) and partially observable mdps (pomdps). We then outline a novel algorithm

this paper, I propose a way of reconciling constrained sorts with the finite domain view of disjunction. My approach is both semantically sound and lends itself to an efficient implementation that preserves incrementality.