Add to ORKGSeveral areas are identifed where machine learning procedures could be employed to substantially improve the quality of practical planners. All of these areas relate to the use of machine learning to define abstraction levels and to control search
Learningshows great promise to extend the generality and effectiveness of planning techniques. Resea...
This paper reports on experiments where techniques of supervised machine learning are applied to the...
COMPOSER is one of a growing number of techniques for learning to plan. Like other approaches, it em...
Outlines an experimental machine learning implementation, called `FM', that applies both explanation...
This chapter is concerned with the enhancement of planning systems using techniques from Machine Lea...
Generating good, production-qualityplans is an essential element in transforming planners from resea...
Machine learning (ML) is often used to obtain control knowledge to improve planning efficiency. Usua...
Attempts to apply classical planning techniques to realistic environments have met with two major d...
This chapter reports the last Machine Learning techniques for the assistance of Automated Planning. ...
As any other problem solving task that employs search, AI Planning needs heuristics to efficiently g...
As any other problem solving task that employs search, AI Planning needs heuristics to efficiently g...
In previous work (Bennett 1993 DeJong and Bennetl 1993) we proposed a machine learning approach call...
We present a novel approach for decreasing state uncertainty in planning prior to solving the planni...
Recent discoveries in automated planning are broadening the scope of planners, from toy problems to ...
International audienceAutomated planning has been a continuous field of study since the 1960s, since...
Learningshows great promise to extend the generality and effectiveness of planning techniques. Resea...
This paper reports on experiments where techniques of supervised machine learning are applied to the...
COMPOSER is one of a growing number of techniques for learning to plan. Like other approaches, it em...
Outlines an experimental machine learning implementation, called `FM', that applies both explanation...
This chapter is concerned with the enhancement of planning systems using techniques from Machine Lea...
Generating good, production-qualityplans is an essential element in transforming planners from resea...
Machine learning (ML) is often used to obtain control knowledge to improve planning efficiency. Usua...
Attempts to apply classical planning techniques to realistic environments have met with two major d...
This chapter reports the last Machine Learning techniques for the assistance of Automated Planning. ...
As any other problem solving task that employs search, AI Planning needs heuristics to efficiently g...
As any other problem solving task that employs search, AI Planning needs heuristics to efficiently g...
In previous work (Bennett 1993 DeJong and Bennetl 1993) we proposed a machine learning approach call...
We present a novel approach for decreasing state uncertainty in planning prior to solving the planni...
Recent discoveries in automated planning are broadening the scope of planners, from toy problems to ...
International audienceAutomated planning has been a continuous field of study since the 1960s, since...
Learningshows great promise to extend the generality and effectiveness of planning techniques. Resea...
This paper reports on experiments where techniques of supervised machine learning are applied to the...
COMPOSER is one of a growing number of techniques for learning to plan. Like other approaches, it em...