Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
Relational databases have had great industrial success in computer science. The power of the paradigm is made clear both by its widespread adoption and by theoretical analysis. Tod...
Abstract. If a CSP instance has no solution, it contains a smaller unsolvable subproblem that makes unsolvable the whole problem. When solving such instance, instead of just return...
One approach to optimal planning is to first start with a sub- optimal solution as a seed plan, and then iteratively search for shorter plans. This approach inevitably leads to an...
Abstract. We describe a way to improve the performance of MDP planners by modifying them to use lower and upper bounds to eliminate non-optimal actions during their search. First, ...
In order to apply constraint programming to a particular domain, the problem must first be modelled as a constraint satisfaction problem. There are typically many alternative mode...
Most algorithms for computing diagnoses within a modelbased diagnosis framework are deterministic. Such algorithms guarantee soundness and completeness, but are NPhard. To overcom...
Alexander Feldman, Gregory M. Provan, Arjan J. C. ...