Report Includes:

  • A general framework for deep Reinforcement Learning (RL) – also known as a semi-supervised learning model in machine learning paradigm
  • Assessing the breadth and depth of RL applications in real-world domains, including increased data efficiency and stability as well as multi-tasking
  • Understanding of the RL algorithm from different aspects; and persuade the decision makers and researchers to put more efforts on RL research