mlsanityData to 7 Oct 2026

LASP: Surveying the State-of-the-Art in Large Language Model-Assisted AI Planning

arXiv 2409.01806 ↗First posted 3 Sep 2024cs.AI cs.CL cs.LGcited by 9

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Abstract (arXiv)

Effective planning is essential for the success of any task, from organizing a vacation to routing autonomous vehicles and developing corporate strategies. It involves setting goals, formulating plans, and allocating resources to achieve them. LLMs are particularly well-suited for automated planning due to their strong capabilities in commonsense reasoning. They can deduce a sequence of actions needed to achieve a goal from a given state and identify an effective course of action. However, it is frequently observed that plans generated through direct prompting often fail upon execution. Our survey aims to highlight the existing challenges in planning with language models, focusing on key areas such as embodied environments, optimal scheduling, competitive and cooperative games, task decomposition, reasoning, and planning. Through this study, we explore how LLMs transform AI planning and provide unique insights into the future of LM-assisted planning.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 39 of its 54 references that are in the map. First posted on arXiv 3 Sep 2024.

Builds on

39 of 54 references.

References · 39

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  2. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
  3. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,317
  4. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,193
  5. 2020ALFWorld: Aligning Text and Embodied Environments for Interactive Learningcited by 1,143
  6. 2022Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agentscited by 1,029
  7. 2023Reasoning with Language Model is Planning with World Modelcited by 846
  8. 2019ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Taskscited by 773
  9. 2023LLM+P: Empowering Large Language Models with Optimal Planning Proficiencycited by 496
  10. 2022MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledgecited by 469
  11. 2018VirtualHome: Simulating Household Activities via Programscited by 411
  12. 2024TravelPlanner: A Benchmark for Real-World Planning with Language Agentscited by 385
27 more
  1. 2022PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Changecited by 372
  2. 2022Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thoughtcited by 334
  3. 2023ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddingscited by 238
  4. 2022Pre-Trained Language Models for Interactive Decision-Makingcited by 220
  5. 2021TEACh: Task-driven Embodied Agents that Chatcited by 194
  6. 2021Benchmarking the Spectrum of Agent Capabilitiescited by 193
  7. 2023AdaPlanner: Adaptive Planning from Feedback with Language Modelscited by 193
  8. 2024VLP: Vision Language Planning for Autonomous Drivingcited by 125
  9. 2024NATURAL PLAN: Benchmarking LLMs on Natural Language Planningcited by 125
  10. 2023SmartPlay: A Benchmark for LLMs as Intelligent Agentscited by 123
  11. 2024Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrappingcited by 89
  12. 2024Can Large Language Models Reason and Plan?cited by 82
  13. 2023Put Your Money Where Your Mouth Is: Evaluating Strategic Planning and Execution of LLM Agents in an Auction Arenacited by 78
  14. 2023ISR-LLM: Iterative Self-Refined Large Language Model for Long-Horizon Sequential Task Planningcited by 77
  15. 2019Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generationcited by 75
  16. 2023SayCanPay: Heuristic Planning with Large Language Models using Learnable Domain Knowledgecited by 49
  17. 2024Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizingcited by 49
  18. 2023Distilling Script Knowledge from Large Language Models for Constrained Language Planningcited by 45
  19. 2023Learning adaptive planning representations with natural language guidancecited by 36
  20. 2023Understanding the Capabilities of Large Language Models for Automated Planningcited by 34
  21. 2022On Grounded Planning for Embodied Tasks with Language Modelscited by 33
  22. 2024Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLMcited by 26
  23. 2023ByteSized32: A Corpus and Challenge Task for Generating Task-Specific World Models Expressed as Text Gamescited by 22
  24. 2024SelfGoal: Your Language Agents Already Know How to Achieve High-level Goalscited by 21
  25. 2024Trust the PRoC3S: Solving Long-Horizon Robotics Problems with LLMs and Constraint Satisfactioncited by 19
  26. 2023Explicit Planning Helps Language Models in Logical Reasoningcited by 12
  27. 2024ITCMA: A Generative Agent Based on a Computational Consciousness Structurecited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 8; 2026: 1.

9 papers.

  1. 2025Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systemscited by 125
  2. 2025PlanGenLLMs: A Modern Survey of LLM Planning Capabilitiescited by 82
  3. 2025LLMs as Planning Formalizers: A Survey for Leveraging Large Language Models to Construct Automated Planning Modelscited by 38
  4. 2025Explain Before You Answer: A Survey on Compositional Visual Reasoningcited by 26
  5. 2025MuSLR: Multimodal Symbolic Logical Reasoningcited by 7
  6. 2025HARBOR: Exploring Persona Dynamics in Multi-Agent Competitioncited by 6
  7. 2025A Survey of Foundation Models for IoT: Taxonomy and Criteria-Based Analysiscited by 5
  8. 2025Towards Pervasive Distributed Agentic Generative AI -- A State of The Artcited by 4
  9. 2026Agentic LLM Planning via Step-Wise PDDL Simulation: An Empirical Characterisationcited by 1

Similar, not cited

Close in wording, no citation either way

  1. 2025Can LLM-Reasoning Models Replace Classical Planning? A Benchmark Study
  2. 2025Large Language Models for Planning: A Comprehensive and Systematic Survey
  3. 2023On the Planning Abilities of Large Language Models (A Critical Investigation with a Proposed Benchmark)
  4. 2025LLMs Can Plan Only If We Tell Them
  5. 2024Understanding the planning of LLM agents: A survey
  6. 2024Chasing Progress, Not Perfection: Revisiting Strategies for End-to-End LLM Plan Generation
  7. 2023On the Planning Abilities of Large Language Models : A Critical Investigation
  8. 2024TwoStep: Multi-agent Task Planning using Classical Planners and Large Language Models