Decentralized Master-Mind: Joint Action Refinement through Iterative Intent Denoising in Multi-Agent Pathfinding

arXiv:2609.32019 · cs.AI, cs.MA · Submitted 2026-09-25 · Read on arXiv

cs.AI, cs.MA

Submitted: 2026-09-25

Updated: 2026-09-25

Code: https://github.com/CognitiveAISystems/DMM

Terminology

• Benchmark — 17× in this paper · explained in 2 episodes
• Fine-Tuning — 12× in this paper · explained in 5 episodes
• Transformer — 11× in this paper · explained in 2 episodes
• Reinforcement Learning — 10× in this paper · explained in 4 episodes
• Ablation — 9× in this paper · explained in 1 episode
• Iterative Refinement — 7× in this paper · explained in 3 episodes
• Diffusion Model — 4× in this paper · explained in 8 episodes
• Diffusion Models — 4× in this paper · explained in 6 episodes
• Repeat-State Escape — 4× in this paper
• Decentralized Master-Mind — 3× in this paper
• Actor — 2× in this paper · explained in 3 episodes
• Core — 2× in this paper · explained in 2 episodes
• Dec-POMDP — 2× in this paper · explained in 2 episodes
• Flow Matching — 2× in this paper · explained in 8 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Hypergraph — 2× in this paper · explained in 2 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Conflict-Based Search (CBS) — 1× in this paper · explained in 2 episodes
• Credit assignment — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• PRIMAL3: Pathfinding via Reinforcement and Imitation Multi-Agent Learning - Leveraging LaCAM3
• Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding
• Discrete Diffusion for Complex and Congested Multi-Agent Path Finding with Sparse Social Attention
• Simulation-Informed Diffusion for Decentralized Multi-robot Motion Planning
• GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization

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