One key decision for heuristic search algorithms is how to balance
exploration and exploitation. In classical planning, novelty search has come
out as the most successful approach in this respect. The idea is to favor
states that contain previously unseen facts when searching for a plan. This is
done by maintaining a record of the tuples of facts observed in previous
states. Then the novelty of a state is the size of the smallest previously
unseen tuple. The most successful version of novelty search is best-first width
search (BFWS), which combines novelty measures with heuristic estimates. An
orthogonal approach to balance exploration-exploitation is to use several
open-lists. These open-lists are ordered using different heuristic estimates,
which diversify the information used in the search. The search algorithm then
alternates between these open-lists, trying to exploit these different
estimates. This is the approach used by LAMA, a classical planner that, a
decade after its release, is still considered state-of-the-art in agile
planning. In this paper, we study how to combine LAMA and BFWS. We show that
simply adding the strongest open-list used in BFWS to LAMA harms performance.
However, we show that combining only parts of each planner leads to a new
state-of-the-art agile planner.

如何将最成功的 BFWS 与经典规划器 LAMA 相结合，我们研究表明，将 BFWS 中强大的 open-list 直接添加到 LAMA 中会降低其性能，但将两者的部分特征相结合却能产生一种新的最先进的敏捷规划器。