Skip to main content
Article thumbnail
Location of Repository

Extending Dynamic Backtracking to Solve Weighted Conditional CSPs

By Robert T. Effinger and Brian C. Williams


Many planning and design problems can be characterized as optimal search over a constrained network of conditional choices with preferences. To draw upon the advanced methods of constraint satisfaction to solve these types of problems, many dynamic and flexible CSP variants have been proposed. One 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 constraints and soft constraints in order to quickly prune infeasible and suboptimal regions of the search space. We provide experimental results on randomly generated WCCSP instances to prove these claims

Year: 2013
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.