The search space in partial-order planning grows quickly with the number of subgoals and initial conditions, as well as less countable factors such as operator ordering and subgoal in teractions. For partial-order planners to solve more than simple problems, the expansion of the search space will need to be controlled. This paper presents four new approaches to controlling search space expansion by exploiting commonalities in emerging plans. These approaches are described in terms of their algorithms, their effect on the completeness and correctness of the underlying planner and their expected performance. The four new and two existing approaches are compared on several metrics of search space and planning overhead.
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