COIN: Collaborative Interaction-Aware Multi-Agent Reinforcement Learning for Self-Driving Systems
COIN: Collaborative Interaction-Aware Multi-Agent Reinforcement Learning for Self-Driving Systems explores A novel MARL framework for self-driving systems that significantly improves safety and efficiency in dense urban traffic through collaborative interaction-aware learning.. Commercial viability score: 8/10 in Multi-Agent Reinforcement Learning for Self-Driving.
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