We present a general unifying framework for sampling-based motion planning under kinematic task constraints which enables a broad class of planners to compute plans that satisfy a given constraint function that encodes, e.g., loop closure, balance, and end-effector constraints. The framework decouples a planner’s method for exploration from constraint satisfaction by representing the implicit c...

We analyze the so-called ppz algorithm for (d, k)-CSP problems for general values of d (number of values a variable can take) and k (number of literals per constraint). To analyze its success probability, we prove a correlation inequality for submodular functions.

The e cient satisfaction of constraints is essential to the performance of constraint-based user interfaces. In the past, most constraint-based user interfaces have used one-way rather than multiway constraints because of a widespread belief that one-way constraints were more e cient. In this paper we argue that many user interface construction problems are handled more naturally and elegantly ...

The purpose of this research is to explore the IPO pricing behavior in an underwriting system by applying the fuzzy game theory. Results of this study are: (1) The application of the fuzzy game theory is more consistent with the uncertainty relationship of human interference between independent and dependent variables in practice with profit return function as a potential function. Rewards for ...

Bone Joint J 2013;95-B, Supple:148–52. Received 7 September 2013; Accepted after revision 8 September 2013 Satisfaction is increasingly employed as an outcome measure for a successful total knee replacement (TKR). Satisfaction as an outcome measure encompasses many different intrinsic and extrinsic factors related to a person’s experience before and after TKR. The Swedish Knee Arthroplasty Regi...

We propose a generic, domain-independent local search method called adaptive search for solving Constraint Satisfaction Problems (CSP). We design a new heuristics that takes advantage of the structure of the problem in terms of constraints and variables and can guide the search more precisely than a global cost function to optimize (such as for instance the number of violated constraints). We a...

We propose a new additive decomposition of probability tables that preserves equivalence of the joint distribution while reducing the size of potentials, without extra variables. We formulate the Most Probable Explanation (MPE) problem in belief networks as a Weighted Constraint Satisfaction Problem (WCSP). Our pairwise decomposition allows to replace a cost function with smaller-arity function...

In this paper the performance of the Hamming-based Reactive Tabu Search algorithm (H-RTS) previously proposed for the Maximum Satiss-ability problem is studied for the diierent Maximum k{Conjunctive Constraint Satisfaction problem. In addition, the use of non-oblivious functions recently proposed in the framework of approximation algorithms is investigated. In particular, two relevant special c...

A general approach to improving constraint solving is to take advantage of information on the structure and particularities of the considered constraints. Specific properties can determine the use of customized solvers, or they can be used to improve solver cooperation and propagation strategies. We propose a framework in which properties are seen as abstractions of the underlying constraints, ...