Muhammad Afzal Upal

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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 approach has been proposed as an alternative technique for improving plan quality. We present a system that automatically learns plan rewriting rules and compare it with a system that(More)
Considerable planning and learning research has been devoted to the problem of automatically acquiring search control knowledge to improve planning e ciency. However, most speed up learning systems de ne planning success rather narrowly, namely as the production of any plan that satis es the goals regardless of the quality of the plan. As planning systems(More)
Considerable planning and learning research has been devoted to the problem of learning domain specific search control rules to improve planning efficiency. There have also been a few attempts to learn search control rules that improve plan quality but such efforts have been limited to state-space planners. The reason being that most of the newer planning(More)
Considerable work has been done to automatically learn domain-specific knowledge to improve the performance of domain independent problem solving systems. However, most of this work has focussed on learning search control knowledge-knowledge that can be used by a problem solving system during search to improve its performance. An alternative approach to(More)