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588,199
Beyond Finite Domains
, 1994
"... 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 problems ..."
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Cited by 41 (3 self)
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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
An OpenEnded Finite Domain Constraint Solver
, 1997
"... 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 encodin ..."
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Cited by 196 (8 self)
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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
Entailment of Finite Domain Constraints
, 1994
"... Using a glassbox theory of finite domain constraints, FD, we show how the entailment of userdefined constraints can be expressed by antimonotone FD constraints. We also provide an algorithm for checking the entailment and consistency of FD constraints. FD is shown to be expressive enough to a ..."
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Cited by 22 (6 self)
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Using a glassbox theory of finite domain constraints, FD, we show how the entailment of userdefined constraints can be expressed by antimonotone 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 on Finite Domains
"... 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 ..."
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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
Simplifiaction of Finite Domain Constraints
, 1998
"... An important issue in Constraint Logic Programming (CLP) systems is how to output constraints in a usable form. Typically, only a small subset ~ x of the variables in constraints is of interest, and so an informal statement of the problem at hand is: given a conjunction C(~x; ~ y) of constraints, e ..."
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Cited by 1 (1 self)
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, 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
Ciphers with Arbitrary Finite Domains
, 2002
"... 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 to t ..."
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Cited by 54 (9 self)
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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
Domain Theory
 Handbook of Logic in Computer Science
, 1994
"... Least fixpoints as meanings of recursive definitions. ..."
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Cited by 546 (25 self)
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Least fixpoints as meanings of recursive definitions.
Hexagonal patterns in finite domains
 Physica D
, 1998
"... 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 t ..."
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Cited by 8 (2 self)
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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
Compiling and Executing Finite Domain Constraints
, 1995
"... : Carlson, B., 1995. Compiling and Executing Finite Domain Constraints. 175 pp. Uppsala Theses in Computing Science 21, ISSN 0283359X, ISBN 9150611003. SICS Dissertation Series 18, ISSN 11011335, ISRN SICSD 18SE. Finite domain constraints are used for specifying and solving complex proble ..."
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Cited by 16 (3 self)
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: Carlson, B., 1995. Compiling and Executing Finite Domain Constraints. 175 pp. Uppsala Theses in Computing Science 21, ISSN 0283359X, ISBN 9150611003. SICS Dissertation Series 18, ISSN 11011335, ISRN SICSD 18SE. Finite domain constraints are used for specifying and solving complex
Planning and acting in partially observable stochastic domains
 ARTIFICIAL INTELLIGENCE
, 1998
"... 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 ..."
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Cited by 1089 (42 self)
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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
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