Control knowledge to improve plan quality
M. Alicia Pérez, Jaime Carbonell · 1994
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 planning control knowledgehas beenaimed at improving the efficiency of planning; this work has been termed "speed-up learning". This paper focuses on learning control knowledge to guide a planner towards better solutions, i.e. to improve the quality of the plans produced by the planner, as its problem solving experience increases. We motivate the use of quality-enhancing search control knowledge and its automated acquisition from problem solving experience. We introduce an implemented mechanism for learning such control knowledge and some of our preliminary results in a process planning domain. Introduction Most research on planning so far has concentrated on methods for constructing sound and complete planners that find a satisficing solution, andonhow to find such solution in an efficient way (Chapman 198...