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Generalizing AI Agents through Task Adaptation
This chapter explores a novel method for training AI agents to generalize across diverse environments by utilizing a parameter vector, as illustrated in the Poet framework. It emphasizes the importance of clear task specifications in reinforcement learning and discusses how human data sets and video resources can accelerate AI learning in complex tasks.