S Chang-Yin, M Chao-Xu - Acta Automatica Sinica, 2020 - aas.net.cn
Reinforcement learning has been used to solve sequence decision problems without models for decades. However, it often faces great challenges in dealing with high …
Abstract While Deep Reinforcement Learning (DRL) has emerged as a promising approach to many complex tasks, it remains challenging to train a single DRL agent that is capable of …
In this paper, a new machine learning framework is developed for complex system control, called parallel reinforcement learning. To overcome data deficiency of current data-driven …