FastDSAC adds a truncated Gaussian policy constraint to distributional actor-critic methods to preserve network plasticity and accelerate training for scalable humanoid locomotion in parallel sampling setups.
The primacy bias in deep reinforcement learning,
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FastDSAC: Enhancing Policy Plasticity via Constrained Exploration for Scalable Humanoid Locomotion
FastDSAC adds a truncated Gaussian policy constraint to distributional actor-critic methods to preserve network plasticity and accelerate training for scalable humanoid locomotion in parallel sampling setups.