Zengxia Guo

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning

Federated reinforcement learning (FRL) methods usually share the encrypted local state or policy information and help each client to learn from others while preserving everyone's privacy. In this work, we propose that sharing the approximated behavior metric-based state projection function is a prom