arXiv (All)
open access
Verifier-Mediated Multi-LLM Coordination for Multi-Robot Path Planning
Foundation models are increasingly used for high-level multi-robot task planning, yet independently generated symbolic plans can become jointly infeasible after geometric grounding because of shared spatial and temporal constraints. We study execution-aware coordination of large-language-model (LLM)
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- SAGE: Symbolic Action-Gating and Editing for LLM Task Planners#1119341
- Beyond Trajectory Imitation: Strategy-Guided Policy Optimization for LLM Reasoning#1342540
- Before Parc Fermé: RL-Time Pruning for Efficient Embodied LLMs in Autonomous Driving#1342503
- LLM+P: Empowering Large Language Models with Optimal Planning Proficiency#16624
- OntoPlan: An Ontology-Grounded Scene Representation and Agentic Framework for Scalable Robot Task Planning#1217024
Record · ID 1296768
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive