Pseudo-Quantized Actor-Critic Algorithm for Robustness to Noisy Temporal Difference Error
Pseudo-Quantized Actor-Critic Algorithm for Robustness to Noisy Temporal Difference Error explores A novel reinforcement learning algorithm that robustly handles noisy temporal difference errors for more stable and efficient learning.. Commercial viability score: 4/10 in Reinforcement Learning.
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