Improving Planning Performance Using Low-Conflict Relaxed Plans
The FF relaxed plan heuristic is one of the most effective techniques in domain-independent satisficing planning and is used by many state-of-the-art heuristic-search planners. However, it may sometimes provide quite inaccurate information, since its relaxation strategy, which ignores the delete effects of actions, may oversimplify a problem's structure. In this paper, we propose a novel algorithm for computing relaxed plans which -- although still relaxed -- aim at respecting much of the structure of the original problem. We accomplish this by generating relaxed plans that attempt to reduce the number of conflicts. An action $a$ will add a conflict when added to a relaxed plan if the resulting plan is provably illegal (i.e, not executable) in the un-relaxed problem. As a second contribution, we propose a new lookahead strategy, in the spirit of Vidal's YAHSP lookahead, that can better exploit the contents of relaxed plans. In our experimental analysis, we show that the resulting heuristic improves over the FF heuristic in a number of domains, most notably when lookahead is enabled. Moreover, the resulting system, which uses our new lookahead, is competitive with state-of-the-art planners, and even better in terms of the number of solved problems.