Hierarchical task network and operator-based planning: two complementary approaches to real-world planning
Tara A. Estlin, Steve Chien, Xuemei Wang · Journal of Experimental & Theoretical Artificial Intelligence · 2001
Work on generative planning systems has focused on two diverse approaches to plan construction. Hierarchical task network (HTN) planners build plans by successively refining high-level goals into lower-level activities. Operator-based planners employ means-end analysis to directly formulate plans consisting of low-level activities. While many have argued the universal dominance of a single approach, this paper presents an alternative view: that in different situations either may be most appropriate. To support this view, a number of advantages and disadvantages of these approaches are described in light of experiences in developing two real-world, fielded planning systems.