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Policy Gradients for Cumulative Prospect Theory in Reinforcement Learning

Lepel, Olivier et al.
arXiv (All) · Papers
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machine-learning
We derive a policy gradient theorem for Cumulative Prospect Theory (CPT) objectives in finite-horizon Reinforcement Learning (RL), generalizing the standard policy gradient theorem and encompassing distortion-based risk objectives as special cases. Motivated by behavioral economics, CPT combines an
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