mlsanityData to 7 Oct 2026

LaMMA-P: Generalizable Multi-Agent Long-Horizon Task Allocation and Planning with LM-Driven PDDL Planner

arXiv 2409.20560 ↗First posted 30 Sep 2024cs.RO cs.AI cs.CVcited by 31

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

Language models (LMs) possess a strong capability to comprehend natural language, making them effective in translating human instructions into detailed plans for simple robot tasks. Nevertheless, it remains a significant challenge to handle long-horizon tasks, especially in subtask identification and allocation for cooperative heterogeneous robot teams. To address this issue, we propose a Language Model-Driven Multi-Agent PDDL Planner (LaMMA-P), a novel multi-agent task planning framework that achieves state-of-the-art performance on long-horizon tasks. LaMMA-P integrates the strengths of the LMs' reasoning capability and the traditional heuristic search planner to achieve a high success rate and efficiency while demonstrating strong generalization across tasks. Additionally, we create MAT-THOR, a comprehensive benchmark that features household tasks with two different levels of complexity based on the AI2-THOR environment. The experimental results demonstrate that LaMMA-P achieves a 105% higher success rate and 36% higher efficiency than existing LM-based multiagent planners. The experimental videos, code, datasets, and detailed prompts used in each module can be found on the project website: https://lamma-p.github.io.

Key facts. Cited by 31 papers in the map (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 21 of its 35 references that are in the map. First posted on arXiv 30 Sep 2024.

Builds on

21 of 35 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024TwoStep: Multi-agent Task Planning using Classical Planners and Large Language Models25 Mar
  2. 2023SMART-LLM: Smart Multi-Agent Robot Task Planning using Large Language Models18 Sep
  3. 2023Building Cooperative Embodied Agents Modularly with Large Language Models5 Jul

Other references · 18

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2024The Llama 3 Herd of Modelscited by 14,192
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  4. 2017AI2-THOR: An Interactive 3D Environment for Visual AIcited by 850
  5. 2023LLM+P: Empowering Large Language Models with Optimal Planning Proficiencycited by 496
  6. 2022PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Changecited by 372
  7. 2023Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planningcited by 204
  8. 2023RoCo: Dialectic Multi-Robot Collaboration with Large Language Modelscited by 171
  9. 2024Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Modelscited by 150
  10. 2023Generalized Planning in PDDL Domains with Pretrained Large Language Modelscited by 139
  11. 2023Translating Natural Language to Planning Goals with Large-Language Modelscited by 132
  12. 2023ISR-LLM: Iterative Self-Refined Large Language Model for Long-Horizon Sequential Task Planningcited by 77
6 more
  1. 2023Dynamic Planning with a LLMcited by 60
  2. 2018Task Planning in Robotics: an Empirical Comparison of PDDL-based and ASP-based Systemscited by 40
  3. 2024LLaMAR: Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environmentscited by 32
  4. 2014An Overview of Hierarchical Task Network Planningcited by 12
  5. 2022Distributed Reinforcement Learning for Robot Teams: A Reviewcited by 11
  6. 2017Cooperative Multi-Agent Planning: A Surveycited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 16; 2026: 15.

31 papers.

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  1. 2025Evaluating LLM-based Agents for Multi-Turn Conversations: A Surveycited by 56
  2. 2025LLMs as Planning Formalizers: A Survey for Leveraging Large Language Models to Construct Automated Planning Modelscited by 38
  3. 2025Embodied AI: From LLMs to World Modelscited by 23
  4. 2025Towards Embodied Agentic AI: Review and Classification of LLM- and VLM-Driven Robot Autonomy and Interactioncited by 18
  5. 2025Teaching LLMs to Plan: Logical Chain-of-Thought Instruction Tuning for Symbolic Planningcited by 15
  6. 2025Generative Multi-Agent Collaboration in Embodied AI: A Systematic Reviewcited by 13
  7. 2025Generalizability of Large Language Model-Based Agents: A Comprehensive Surveycited by 10
  8. 2025REMAC: Self-Reflective and Self-Evolving Multi-Agent Collaboration for Long-Horizon Robot Manipulationcited by 8
  9. 2025Benchmarking LLMs' Swarm intelligencecited by 8
  10. 2025PGPO: Enhancing Agent Reasoning via Pseudocode-style Planning Guided Preference Optimizationcited by 8
  11. 2025Adaptive Domain Modeling with Language Models: A Multi-Agent Approach to Task Planningcited by 6
  12. 2025HEAL: An Empirical Study on Hallucinations in Embodied Agents Driven by Large Language Modelscited by 5
19 more
  1. 2026Drive My Way: Preference Alignment of Vision-Language-Action Model for Personalized Drivingcited by 4
  2. 2025Compositional Coordination for Multi-Robot Teams with Large Language Modelscited by 3
  3. 2025SENTINEL: A Multi-Level Formal Framework for Safety Evaluation of Foundation Model-based Embodied Agentscited by 2
  4. 2025PIP-LLM: Integrating PDDL-Integer Programming with LLMs for Coordinating Multi-Robot Teams Using Natural Languagecited by 2
  5. 2026Priority-Aware Multi-Robot Coverage Path Planningcited by 2
  6. 2026KGLAMP: Knowledge Graph-guided Language model for Adaptive Multi-robot Planning and Replanningcited by 2
  7. 2026CommCP: Efficient Multi-Agent Coordination via LLM-Based Communication with Conformal Predictioncited by 2
  8. 2026Hierarchical LLM-Based Multi-Agent Framework with Prompt Optimization for Multi-Robot Task Planningcited by 2
  9. 2026SafeGen-LLM: Enhancing Safety Generalization in Task Planning for Robotic Systemscited by 2
  10. 2026BrainMem: Brain-Inspired Evolving Memory for Embodied Agent Task Planningcited by 2
  11. 2026Scale-Plan: Scalable Language-Enabled Task Planning for Heterogeneous Multi-Robot Teamscited by 1
  12. 2026A Closed-Loop Multi-Agent Framework for Robust Multi-Robot Manipulationcited by 1
  13. 2026Mosaic: Runtime-Efficient Multi-Agent Embodied Planningcited by 1
  14. 2025Transforming Monolithic Foundation Models into Embodied Multi-Agent Architectures for Human-Robot Collaborationcited by 0
  15. 2026LLM-Grounded Dynamic Task Planning with Hierarchical Temporal Logic for Human-Aware Multi-Robot Handovercited by 0
  16. 2026Object Search in Partially-Known Environments via LLM-informed Model-based Planning and Prompt Selectioncited by 0
  17. 2026NEXUS: Continual Learning of Symbolic Constraints for Safe and Robust Embodied Planningcited by 0
  18. 2026Communication-Efficient Digital-Twin Coordination for Heterogeneous LLM Embodied Agents over Computing Power Networkscited by 0
  19. 2026Systematic Multi-Agent Vision-and-Language Navigation: Formulation, Benchmark, and Methodcited by 0

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  7. 2025A Systematic Study of Large Language Models for Task and Motion Planning With PDDLStream
  8. 2024Understanding the planning of LLM agents: A survey