TR029: Constraint Propagation in Planning

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Abstract/Contents

Abstract: Constraint propagation is a deductive activity performed by a constraint propagation system for a problem-solver. It enables the problem-solver to decompose a problem without neglecting interactions between subproblems, determine which subproblems are the most constrained and focus attention accordingly. Constraint propagation techniques are often used to solve planning and scheduling problems. Experiments reported in the past have shown the interest of these techniques in the planning and scheduling domain. In this report, we review various constraint propagation techniques and provide experimental results allowing to compare them on a variety of problems. We conclude that current constraint propagation systems do not enable a human problem-solver to make his (or her) own applications as efficient as possible without the help of a specialist. An interesting avenue of research is to make the adaptation of a generic constraint propagation system manageable by its users. Another is to provide the system with the ability to learn from its experience and adapt itself to the type of planning and scheduling problems it encounters.

Type of resource	text
Date created	January 1991

Author	Le Pape, Claude

Subject	CIFE
Subject	Center for Integrated Facility Engineering
Subject	Stanford University
Subject	Constraint Propagation
Subject	Incremental Problem-Solving
Subject	Planning
Subject	Predictive Problem-Solving
Subject	Reactive Problem-Solving
Subject	Scheduling
Genre	Technical report

Location	https://purl.stanford.edu/rx233qx1158

Use and reproduction: User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.

Preferred Citation: Le Pape, Claude. (1991). TR029: Constraint Propagation in Planning. Stanford Digital Repository. Available at: http://purl.stanford.edu/rx233qx1158

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