Integrating planning and learning: The Prodigy architecture
Journal of Experimental
and Theoretical Artificial Intelligence, 7(1), pages 81-120, 1995.
Abstract
Planning is a complex reasoning task that is well suited for the study
of improving performance and knowledge by learning, i.e. by accumulation
and interpretation of planning experience. Prodigy is an architecture that
integrates planning with multiple learning mechanisms. Learning occurs
at the planner's decision points and integration in Prodigy is achieved
via mutually interpretable knowledge structures. This article describes
the Prodigy planner, briefly reports on several learning modules developed
earlier along the project, and presents in more detail two recently explored
methods to learn to generate plans of better quality. We introduce the
techniques, illustrate them with comprehensive examples, and show prelimary
empirical results. The article also includes a retrospective discussion
of the characteristics of the overall Prodigy architecture and discusses
their evolution within the goal of the project of building a large and
robust integrated planning and learning system.