There has been substantial recent interest in two new families of search techniques. One family consists of nonsystematic methods such as gsat; the other contains systematic approaches that use a polynomial amount of justification information to prune the search space. This paper introduces a new technique that combines these two approaches. The algorithm allows substantial freedom of movement in the search space but enough information is retained to ensure the systematicity of the resulting analysis. Bounds are given for the size of the justification database and conditions are presented that guarantee that this database will be polynomial in the size of the problem in question. 1 INTRODUCTION The past few years have seen rapid progress in the development of algorithms for solving constraintsatisfaction problems, or csps. Csps arise naturally in subfields of AI from planning to vision, and examples include propositional theorem proving, map coloring and scheduling problems. The probl...

satisfaction problem. This algorithm makes use of some of the good properties of centralised dynamic backtracking. It ensures the completeness of search, and allows a high level of asynchronism by sidestepping the unnecessary addition of links. 1.

Abstract. Dynamic Backtracking (DBT) is a well known algorithm for solving Constraint Satisfaction Problems. In DBT, variables are allowed to keep their assignment during backjump, if they are compatible with the set of eliminating explanations. A previous study has shown that when DBT is combined

RecentlyFtwo new backtracking algorithmsF dynamic backtracking (DB) and partial order dynamic backtrack-ing (PDB) have been presented. These algorithms have the property to be additive on disjoint subproblems and yet use only polynomial space. Unlike DBFPDB only im-poses a partial search order

processes are generated dynamically, started by the initializing agent, and by any number of agents during search. In the proposed, ConcDB, algorithm, all search processes perform dynamic backtracking. As a consequence of dynamic backtracking, a search space scanned by one search process can be found

introduced to represent them. In spite of its name, the recent Dynamic Backtracking algorithm proposed in (Ginsberg 1993) does not solve dynamic CSPs, but static ones. But its nogood recording and backtracking mechanisms are very interesting in the DCSP framework. In this paper, we propose an extension

Recent works on constraint relaxation [Jussien, 1997; Jussien and Boizumault, 1997b] provided the decorum system (Deduction-based Constraint Relaxation Management). That system can be seen as an integration of arc-consistency within the dynamic backtracking algorithm [Ginsberg, 1993]. Dynamic

Most of complete search algorithms over Constraint Satisfaction Problems (csp) are based on Standard Backtracking. Two main

This paper investigates a simple, constructive search strategy: an incomplete version of Ginsberg's Dynamic Backtracking which records no information during search, and randomly selects variables for backtracking. Combining this with forward checking and dynamic variable ordering heuristics we

such variant is the Weighted Conditional CSP (WCCSP). So far, however, little work has been done to extend the full suite of CSP search algorithms to solve these CSP variants. In this paper, we extend Dynamic Backtracking and similar backjumpingbased CSP search algorithms to solve WCCSPs by utilizing activity