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Meta-Reinforcement Learning Framework MAGE Enables LLM Agents to Adapt and Strategize
Researchers have proposed MAGE, a meta-reinforcement learning framework that enables large language model agents to adapt and strategize in dynamic environments. Unlike existing approaches that struggle with long-term adaptation, MAGE embeds the learning process directly within the model by integrating interaction histories and reflections into the context window.