Distributional Reinforcement Learning: Why Predicting a Distribution Beats Predicting a Mean
Most reinforcement learning starts with a single number. For a state and an action, the agent learns the expected return: the average of all the futures that could follow. That average is useful, but it hides almost everything interesting about risk, luck, and multimodality. Two policies can have t…
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- 2026-11-01 02:14 · DEV Community — Machine Learning
Distributional Reinforcement Learning: Why Predicting a Distribution Beats Predicting a Mean