TL;DR: The primary aim is to provide an accessible, unified framework, within which to present the algorithms including a new path consistency algorithm, to discuss their relationships and the may applications, both realized and potential of network consistency algorithms.
TL;DR: In this article, the min-conflicts heuristic is used to minimize the number of constraint violations after each step in a value-ordering heuristic search, which can be used with a variety of different search strategies.
TL;DR: New algorithms for arc and path consistency are presented and it is shown that the arc consistency algorithm is optimal in time complexity and of the same-order space complexity as the earlier algorithms.
TL;DR: In this article, the authors proposed a new algorithm, AC-6, which keeps the optimal worst-case time complexity of AC-4 while working out the drawback of space complexity.
TL;DR: Evidence is presented that a constraint programming approach to planning does indeed work well and has the advantage in terms of time and space efficiency over the current state-of-the-art planners.
Abstract: Constraint programming, a methodology for solving difficult combinatorial problems by representing them as constraint satisfaction problems, has shown that a general purpose search algorithm based on constraint propagation combined with an emphasis on modeling can solve large, practical scheduling problems. Given the success of constraint programming on scheduling problems and the similarity of scheduling to planning, the question arises, would a constraint programming approach work as well in planning? In this paper, we present evidence that a constraint programming approach to planning does indeed work well and has the advantage in terms of time and space efficiency over the current state-of-the-art planners.