Dynamic heuristic planner selection
Brian Cook, Manfred Huber · 2016
Heuristic search is considered state-of-the-art for classical planning. However, the performance of search heuristics varies significantly from problem to problem and no single heuristic is superior to all others. As a result, it is highly desirable to identify and utilize the best available heuristic for a particular planning problem. This paper presents a novel approach for planning that monitors the search dynamics of a heuristic planner over time in order to recognize whether the planner is making progress toward a solution. It then dynamically selects from a set of heuristic planners during the planning process so that planners that appear to be making progress are allocated more processor time. Experimental results show this approach is more effective than static approaches of dividing processor time equally between planners or selecting any one planner a priori.