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Mitigating Plasticity Loss in On-Policy RL by devilevilsn is a document available to read on EtoBox.
What is Mitigating Plasticity Loss in On-Policy RL about?
This study investigates plasticity loss in on-policy deep reinforcement learning (RL), where neural networks struggle to adapt to new tasks over time. The authors conduct experiments to show that traditional mitigation methods from supervised and off-policy learning often fail in this context, while
- Author
- devilevilsn
- Language
- EN