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多模态强化学习

多模态强化学习通过感知和整合多种输入模态（例如原始像素、语言指令、音频和本体感受传感器）来训练智能体做出序列决策。智能体不是在单一数据流上进行操作，而是将异构信号融合到统一的状态表示中，并通过环境奖励反馈学习策略。

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多模态强化学习
多模态图神经网络多模态Transformer多模态视觉变换器强化学习自监督强化学习迁移学习与强化学习 (Transfer RL)…

来源

  1. Reed, S., Zolna, K., Parisotto, E., Colmenarejo, S. G., Novikov, A., Barth-Maron, G., ... & de Freitas, N. (2022). A Generalist Agent. Transactions on Machine Learning Research. link ↗
  2. Multimodal learning. Wikipedia. link ↗

如何引用本页

ScholarGate. (2026, June 3). Multimodal Reinforcement Learning (Multi-Sensory RL Agent Learning). ScholarGate. https://scholargate.app/zh/deep-learning/multimodal-reinforcement-learning

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ScholarGate — Multimodal Reinforcement Learning (Multimodal Reinforcement Learning (Multi-Sensory RL Agent Learning)). 于 2026-06-15 检索自 https://scholargate.app/zh/deep-learning/multimodal-reinforcement-learning · 数据集： https://doi.org/10.5281/zenodo.20539026