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. ...
In this paper we consider three di erent kinds of domain dependent control knowledge (temporal, procedural and HTN-based) that are useful in planning. Our approach is declarative ...
Tran Cao Son, Chitta Baral, Tran Hoai Nam, Sheila ...
Over the years increasingly sophisticated planning algorithms have been developed. These have made for more efficient planners, but unfortunately these planners still suffer from ...
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...
Heuristic search procedures are useful in a large number of problems of practical importance. Such procedures operate by searching several paths in a search space at the same time...
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...
Aimsof traditional planners had beenlimited to finding a sequenceof operators rather than finding an optimal or neax-optimalfinal state. Consequent]y, the performanceimprovementsy...
The utility problem occurs when the cost of the acquired knowledge outweighs its bene ts. When the learner acquires control knowledge for speeding up a problem solver, the bene t ...
Machine learning (ML) is often used to obtain control knowledge to improve planning efficiency. Usually, ML techniques are used in isolation from experience that could be obtained...
Learning capabilities of computer systems still lag far behind biological systems. One of the reasons can be seen in the inefficient re-use of control knowledge acquired over the...