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SARA
2007
Springer
10 years 7 months ago
Active Learning of Dynamic Bayesian Networks in Markov Decision Processes
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...
Anders Jonsson, Andrew G. Barto
SARA
2007
Springer
10 years 7 months ago
Reformulation for Extensional Reasoning
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...
Timothy L. Hinrichs, Michael R. Genesereth
SARA
2007
Springer
10 years 7 months ago
Boosting MUS Extraction
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...
Santiago Macho González, Pedro Meseguer
SARA
2007
Springer
10 years 7 months ago
A Meta-CSP Model for Optimal Planning
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...
Peter Gregory, Derek Long, Maria Fox
SARA
2007
Springer
10 years 7 months ago
Computing and Using Lower and Upper Bounds for Action Elimination in MDP Planning
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, ...
Ugur Kuter, Jiaqiao Hu
SARA
2007
Springer
10 years 7 months ago
Tailoring Solver-Independent Constraint Models: A Case Study with Essence' and Minion
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...
Ian P. Gent, Ian Miguel, Andrea Rendl
SARA
2007
Springer
10 years 7 months ago
Approximate Model-Based Diagnosis Using Greedy Stochastic Search
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. ...
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