LC-MAPF uses multi-round local communication between neighboring agents in a pre-trained model to outperform prior learning-based MAPF solvers on diverse unseen scenarios while preserving scalability.
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cs.AI 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
AI agents in supply chain simulations outperform humans but exhibit decision instability that GRPO post-training reduces.
citing papers explorer
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Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding
LC-MAPF uses multi-round local communication between neighboring agents in a pre-trained model to outperform prior learning-based MAPF solvers on diverse unseen scenarios while preserving scalability.
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Reliability and Effectiveness of Autonomous AI Agents in Supply Chain Management
AI agents in supply chain simulations outperform humans but exhibit decision instability that GRPO post-training reduces.