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Jen-Yen Chang

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Preprint Jul 2026

Learning the Supports for Categorical Critic in Reinforcement Learning

This work investigates the Gaussian Histogram Loss (HL-Gauss), a recent approach that reframes value estimation as classification by encoding each scalar Bellman target as a Gaussian-smoothed categorical target, and derives an objective that forms an upper bound on the mean-squared Bellman error.

Jen-Yen Chang, Takayuki Osa, Tatsuya Harada · 0 citations