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AAAI 2026official proceedings

Inapproximability of STRIPS Planning

Xing Tan, Alban Grastien

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.1609/aaai.v40i43.40961 ↗

摘要

Automated planning involves finding a sequence of actions that changes the world from an initial state to a final state with goals satisfied. The general problem is PSPACE-hard. Nevertheless, many restricted variants are NP-complete or even in P. Existing complexity work focuses mostly on plan existence, or plan with minimal plan length. Little is known about optimization variants that aim to satisfy as many goal conditions as possible. In this paper, we aim to fill this gap by providing a first inapproximability study of goal-maximization using the classical STRIPS formalism. For MAXPLANSAT and its length-bounded counterpart MAXPLANSAT(K), we prove tight constant-factor lower bounds. More specifically, through performing L-reductions from MAXE3SAT and MAX3DM, we show several of these problems are inapproximable by a constant factor, unless P=NP.