As any other problem solving task that employs search, AI Planning needs heuristics to efficiently guide the problem-space exploration. Machine learning (ML) provides several tec...
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, ...
The set of partially interdependent lexical and syntactic decisions that have to be made in the process of natural language generation are best seen as a complex planning and sear...
In this paper we describe SINERGY, which is a highly parallelizable, linear planning system that is based on the genetic programming paradigm. Rather than reasoning about the world...
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...