Critic complexity quantified by spectral effective-rank entropy is measurable during TD3/PPO training, associated with behavior in a heterogeneous way, and can be altered by adding a spectral-entropy penalty to the critic loss.
Deep Reinforcement Learning with Double Q-learning
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Gauging, Measuring, and Controlling Critic Complexity in Actor-Critic Reinforcement Learning
Critic complexity quantified by spectral effective-rank entropy is measurable during TD3/PPO training, associated with behavior in a heterogeneous way, and can be altered by adding a spectral-entropy penalty to the critic loss.