The paper explores the combination of the LAMA and Best-First Width Search (BFWS) planning algorithms to achieve improved performance in agile planning, where the goal is to find plans as quickly as possible without considering plan quality.
The authors first attempt to simply add the strongest open-list used in BFWS(f6) to LAMA, but find that this combination actually harms performance compared to the individual planners. However, a detailed ablation study reveals that selectively removing certain features from LAMA and BFWS can lead to significant improvements.
The authors propose a new planner called NOLAN that consolidates the open-lists from LAMA and the novelty-based open-list from BFWS(f hLM
2
). NOLAN outperforms all other state-of-the-art agile planners, including the winners of the previous International Planning Competitions (IPCs), by a large margin, achieving a 13% higher agile score than the second-best method.
The key insights are:
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arxiv.org
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