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Finally, Table 3 illustrates the PPO hyperparameters, which remain fixed throughout all the experiments · 2018

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cs.LG 1

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2025 1

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CONDITIONAL 1

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Adaptive Data Exploitation in Deep Reinforcement Learning

cs.LG · 2025-01-22 · conditional · novelty 4.0

Adaptively lowering the number of per-episode update epochs via a multi-armed bandit improves or matches PPO/DrAC returns on standard benchmarks while reducing training FLOPS.

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  • Adaptive Data Exploitation in Deep Reinforcement Learning cs.LG · 2025-01-22 · conditional · none · ref 50

    Adaptively lowering the number of per-episode update epochs via a multi-armed bandit improves or matches PPO/DrAC returns on standard benchmarks while reducing training FLOPS.