In this paper we introduce a variant of the quantiier elimination problem for the rst order theory of real closed elds. Instead of considering a single quantiied formula, we consider a uniform sequence of such formulas and eliminate quantiiers to obtain another uniform sequence. Our immediate motivation comes from a problem in the theory of constraint databases with real polynomial constraints....

Dynamic detection and elimination of symmetry in constraints, is in general a hard task, but in Not-Equals binary constraint networks, the symmetry conditions can be simplified. In this paper, we extend the principle of symmetry to dominance in Not-Equals Constraint Networks and show how dominated values are detected and eliminated at each node of the search tree. A Linear time complexity algor...

Constraint logic programming combines Horn-clause logic and constraint reasoning. However, the specification of many problems often requires disjunctive, i.e. non-Horn rules in addition. There are approaches proposing such an extension of logic programming, but first and foremost they provide theoretical frameworks only. Here, we want to introduce a method which is also well-suited for implemen...

Variable Elimination (VE) is the most basic one of many Bayesian network inference algorithms. The speed and complexity reasoning mainly depend on order elimination. Finding optimal elimination a Nondeterministic Polynomial Hard (NP-Hard) problem, which often solved by heuristic search in practice. In to improve variable method, minimum, maximum potential, minimum missing edge added methods are...

We model the algorithmic task of geometric elimination (e.g., quantifier elimination in the elementary field theories of real and complex numbers) by means of certain constraint database queries, called geometric queries. As a particular case of such a geometric elimination task, we consider sample point queries. We show exponential lower complexity bounds for evaluating geometric queries in th...

Elimination of illumination color in color images is essential for various fields in computer vision. Many methods have been proposed to solve it, however there are few methods employing varying illumination as a constraint. We found Finlayson et al. ’s method [10] applicable for natural images, and extended it by making the reference illumination variable. To evaluate our method, we have condu...

Adaptive consistency is a solving algorithm for constraint networks. Its basic step is variable elimination: it takes a network as input, and produces an equivalent network with one less variable and one new constraint (the join of the variable bucket). This process is iterated until every variable is eliminated, and then all solutions can be computed without backtracking. A direct, naive imple...