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» Learning Control Knowledge for Forward Search Planning
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JMLR
2008
124views more  JMLR 2008»
10 years 2 months ago
Learning Control Knowledge for Forward Search Planning
A number of today's state-of-the-art planners are based on forward state-space search. The impressive performance can be attributed to progress in computing domain independen...
Sung Wook Yoon, Alan Fern, Robert Givan
ICML
1996
IEEE
11 years 3 months ago
Representing and Learning Quality-Improving Search Control Knowledge
Generating good, production-quality plans is an essential element in transforming planners from research tools into real-world applications, but one that has been frequently overl...
M. Alicia Pérez
IJCAI
2001
10 years 4 months ago
Planning with Resources and Concurrency: A Forward Chaining Approach
Recently tremendous advances have been made in the performance of AI planning systems. However increased performance is only one of the prerequisites for bringing planning into th...
Fahiem Bacchus, Michael Ady
AIPS
1994
10 years 4 months ago
Control Knowledge to Improve Plan Quality
Generating production-quality plans is an essential element in transforming planners from research tools into real-world applications. However most of the work to date on learning...
M. Alicia Pérez, Jaime G. Carbonell
AI
2000
Springer
10 years 7 months ago
Learning Rewrite Rules versus Search Control Rules to Improve Plan Quality
Domain independent planners can produce better-quality plans through the use of domain-speci c knowledge, typically encoded as search control rules. The planning-by-rewriting appro...
Muhammad Afzal Upal, Renee Elio
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