TIMRL: A Novel Meta-Reinforcement Learning Framework for Non-Stationary and Multi-Task Environments

Chenyang Qi, Huiping Li, Panfeng Huang

In recent years, meta-reinforcement learning (meta-RL) algorithm has been proposed to improve sample efficiency in the field of decision-making and control, enabling agents to lear…