Refinement planning as a unifying framework for plan synthesis

Planning - the ability to synthesize a course of action to achieve desired goals - is an important part of intelligent agency and has thus received significant attention within AI for more than 30 years. Work on efficient planning algorithms still continues to be a hot topic for research in AI and has led to several exciting developments in the past few years. This article provides a tutorial introduction to all the algorithms and approaches to the planning problem in AI. To fulfill this ambitious objective, I introduce a generalized approach to plan synthesis called refinement planning and show that in its various guises, refinement planning subsumes most of the algorithms that have been, or are being, developed. It is hoped that this unifying overview provides the reader with a brand-name-free appreciation of the essential issues in planning.