Abstract Solvers for constraint optimisation problems exploit variable and value ordering heuristics. Numerous expert-designed heuristics exist, while recent research learns novel, customised from past problem instances. This article addresses unseen which no historical data is available. We propose one-shot learning of customised, instance-specific To do so, we introduce the concept deep , a d...

Coarse-grained arc consistency algorithms like AC-3, AC-3d, and AC-2001, are efficient when it comes to transforming a Constraint Satisfaction Problem (CSP) to its arc consistent equivalent. These algorithms repeatedly carry out revisions to remove unsupported values from the domains of the variables. The order of these revisions is determined by so-called revision ordering heuristics. In this ...

The usual way for solving constraint satisfaction problems is to use a backtracking algorithm One of the key factors in its e ciency is the rule it will use to decide on which variable to branch next namely the variable ordering heuristics In this paper we attempt to give a general formulation of dynamic variable ordering heuristics that take into account the properties of the neighborhood of t...

of Nonholonomic Wheeled Mobile Robot Hyun-Sik Shim Jong-Hwan Kim Kwangill Koh Dept. of Elec. Eng. Dept. of Elec. Eng. KAIST KAIST LG Industrial Systems Co., Ltd. Taejoen-shi, 305-701, Korea Taejoen-shi, 305-701, Korea Kyongki-do, 430-080, Korea [email protected] [email protected] [email protected] Abstract A variable structure controller(VSC) for a nonholonomic wheeled mobile...

Adding symmetry breaking constraints is one of the oldest ways of breaking variable symmetries for CSPs. For instance, it is well known that all the symmetries for the pigeon hole problem can be removed by ordering the variables. We have generalized this result to all CSPs where the variables are subject to an all different constraint. In such case it is possible to remove all variable symmetri...

Cylindrical algebraic decomposition(CAD) is a key tool in computational algebraic geometry, particularly for quantifier elimination over real-closed fields. When using CAD, there is often a choice for the ordering placed on the variables. This can be important, with some problems infeasible with one variable ordering but easy with another. Machine learning is the process of fitting a computer m...

Fault tree analysis is a commonly used technique to assess the systems reliability performance in terms of its components reliability characteristics. More recently, the Binary Decision Diagram (BDD) methodology has been introduced which significantly aids the analysis of the fault tree diagram. The approach has been shown to improve both the efficiency of determining the minimal cut sets of th...

We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable ordering, it only requires polynomial time conditional independence tests and learns the exact structure theoretically. A variant which adopts the Bayesian Dirichlet scoring function is also presented for practical purposes...

We describe a new partial symmetry breaking method that can be used to break arbitrary variable/value symmetries in combination with depth first search, static value ordering and dynamic variable ordering. The main novelty of the method is a new dominance detection technique based on local search in the symmetry group. It has very low time and memory requirements, yet in preliminary experiments...