AINeutralarXiv – CS AI · 3h ago6/10
🧠
Personalized Observation Normalization for Federated Reinforcement Learning in Simulation Environments with Heterogeneity
Researchers propose a Personalized Observation Normalization (PON) method to address challenges in federated reinforcement learning across heterogeneous environments. The technique allows individual agents to maintain localized normalization statistics while collaborating on a shared policy, improving training efficiency and performance without compromising privacy.