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PlanGenLLMs: A Modern Survey of LLM Planning Capabilities

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arxiv 2502.11221 v3 pith:PZFIAG2K submitted 2025-02-16 cs.AI cs.CL

PlanGenLLMs: A Modern Survey of LLM Planning Capabilities

Hui Wei , Zihao Zhang , Shenghua He , Tian Xia , Shijia Pan , Fei Liu This is my paper
classification cs.AI cs.CL
keywords planningcriteriallmsmakingstatesurveytasksagentic
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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LLMs have immense potential for generating plans, transforming an initial world state into a desired goal state. A large body of research has explored the use of LLMs for various planning tasks, from web navigation to travel planning and database querying. However, many of these systems are tailored to specific problems, making it challenging to compare them or determine the best approach for new tasks. There is also a lack of clear and consistent evaluation criteria. Our survey aims to offer a comprehensive overview of current LLM planners to fill this gap. It builds on foundational work by Kartam and Wilkins (1990) and examines six key performance criteria: completeness, executability, optimality, representation, generalization, and efficiency. For each, we provide a thorough analysis of representative works and highlight their strengths and weaknesses. Our paper also identifies crucial future directions, making it a valuable resource for both practitioners and newcomers interested in leveraging LLM planning to support agentic workflows.

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Cited by 2 Pith papers

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  2. Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures

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