稳定报道时间 2026-10-02 12:00
面向自动驾驶快速适应的元多智能体强化学习
一个新的元多智能体强化学习框架被引入，用于多智能体系统中交互策略的快速适应，应用于自动驾驶领域。
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证据
- AarXiv cs.AI一手来源2026-10-02 12:00
> Abstract: This paper develops a meta-multi-agent reinforcement learning (meta-MARL) framework to enable fast adaptation of interactive policies in a multi-agent system (MAS).
- AarXiv cs.AI一手来源2026-10-02 12:00
Abstract: This paper develops a meta-multi-agent reinforcement learning (meta-MARL) framework to enable fast adaptation of interactive policies in a multi-agent system (MAS). Meta-reinforcement learning (meta-RL) enables agents to rapidly adapt to new tasks/environments using a bi-level optimization mechanism. However, existing meta-RL generally focuses on single-agent systems.