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AAAI
1994
13 years 10 months ago
Learning Explanation-Based Search Control Rules for Partial Order Planning
This paper presents snlp+ebl, the first implementation of explanation based learning techniques for a partial order planner. We describe the basic learning framework of snlp+ebl, ...
Suresh Katukam, Subbarao Kambhampati
AI
2000
Springer
14 years 1 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
AAI
2005
117views more  AAI 2005»
13 years 9 months ago
Machine Learning in Hybrid Hierarchical and Partial-Order Planners for Manufacturing Domains
The application of AI planning techniques to manufacturing systems is being widely deployed for all the tasks involved in the process, from product design to production planning an...
Susana Fernández, Ricardo Aler, Daniel Borr...
AI
1999
Springer
13 years 9 months ago
Learning Action Strategies for Planning Domains
There are many different approaches to solving planning problems, one of which is the use of domain specific control knowledge to help guide a domain independent search algorithm. ...
Roni Khardon
GECCO
2005
Springer
130views Optimization» more  GECCO 2005»
14 years 2 months ago
ATNoSFERES revisited
ATNoSFERES is a Pittsburgh style Learning Classifier System (LCS) in which the rules are represented as edges of an Augmented Transition Network. Genotypes are strings of tokens ...
Samuel Landau, Olivier Sigaud, Marc Schoenauer