方法证据记录
Multilingual Reinforcement Learning
Multilingual Reinforcement Learning applies the RL paradigm — an agent learning by interaction and reward — to environments that involve multiple languages. The agent must interpret multilingual observations, follow cross-lingual instructions, or generalize policies trained in one language to new target languages, making it applicable to cross-lingual dialogue, multilingual game-playing agents, and language-grounded sequential decision tasks.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Multilingual Reinforcement Learning (Cross-Lingual RL for NLP and Language Grounding)
分类方法记录 · ml-model / deep-learning
- Sutton, R. S., & Barto, A. G. (1998). Reinforcement Learning: An Introduction. MIT Press. · ISBN 978-0262193986
- Reinforcement learning. Wikipedia. · URL
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