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Reinforcement learning (RL) is one of the foundational pillars of artificial intelligence and machine learning. An important consideration in any optimization or control problem is the notion of risk, but its incorporation into RL has been a recent development. This monograph surveys research on risk-sensitive RL that uses policy gradient search.
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