提出部分接地编码，让规划更高效且支持长序列任务。
When both Grounding and not Grounding are Bad -- A Partially Grounded Encoding of Planning into SAT (Extended Version)
- 动作保持抽象，仅部分谓词接地，平衡效率与表达力。
- 规划长度增加时，求解时间线性增长，优于旧方法的平方级增长。
- 适合处理难以完全接地的复杂规划问题，如工业调度场景。
经典规划问题通常采用一阶逻辑表示，具有紧凑性和通用性。尽管多数规划器会将这些表示完全接地以简化推理，但可能导致规模呈指数级膨胀。近期方法则直接在抽象层面操作，避免完整接地。本文探索介于完全抽象与完全接地之间的中间路径，提出三种SAT编码方法：保留动作抽象，仅部分接地谓词。不同于以往在计划长度上呈二次方扩展的SAT编码，本方法实现线性扩展，显著提升长计划求解性能。实验表明，在难以接地的复杂领域中，其最优编码在长度最优规划任务上超越当前最先进方法。
原文摘要 · Abstract (English)
Classical planning problems are typically defined using lifted first-order representations, which offer compactness and generality. While most planners ground these representations to simplify reasoning, this can cause an exponential blowup in size. Recent approaches instead operate directly on the lifted level to avoid full grounding. We explore a middle ground between fully lifted and fully grounded planning by introducing three SAT encodings that keep actions lifted while partially grounding predicates. Unlike previous SAT encodings, which scale quadratically with plan length, our approach scales linearly, enabling better performance on longer plans. Empirically, our best encoding outperforms the state of the art in length-optimal planning on hard-to-ground domains.
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