We show that global constraints on finite domains like alldifferent can be reformulated into answer set programs on which we achieve arc, bound or range consistency. These reform...
Finite domain propagation solvers effectively represent the possible values of variables by a set of choices which can be naturally modelled as Boolean variables. In this paper we...
Theefficiency of algorithmsfor probabilistic inference in Bayesian networks can be improvedby exploiting independenceof causal influence. Thefactorized representation of independe...
We propose a method for local search of Boolean relations relating variables of a CNF formula. The method is to branch on small subsets of the set of CNF variables and to analyze ...
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...