On the morning of March 7, 2024, Secretary Gao Yang of the school invited Dr. Hao Jianye, Associate Professor of the Department of Intelligent Computing at Tianjin University and Director of Huawei Noah Decision Reasoning Laboratory, to deliver a report titled Challenges and Implementation of Deep Reinforcement Learning.
Abstract: This report will first introduce the background of deep reinforcement learning, and then introduce the challenges and corresponding solutions faced by deep reinforcement learning from three aspects: how to learn well, learn quickly, and learn steadily. At the same time, it will introduce the practical applications in scenarios such as autonomous driving, EDA chip design, and robotics.
Reporter Introduction: Dr. Hao Jianye, Associate Professor of the Department of Intelligent Computing at Tianjin University, and Director of Huawei Noah Decision Reasoning Laboratory. My main research areas are deep reinforcement learning and multi-agent systems. Published over 100 international conferences and journal papers in the field of artificial intelligence, as well as 2 monographs. I have led more than 10 projects, including the 2030 Major Artificial Intelligence Project of the Ministry of Science and Technology of China, the Major Artificial Intelligence Cultivation Project of the National Natural Science Foundation of China, and the Key National Defense Science and Technology Innovation Project. My research results have won the Best Paper Award at international conferences three times, and I have won four championships in the NeuroIPS20-22 conference competition. The relevant achievements have been applied in the fields of industrial basic software intelligence, autonomous driving, game AI, advertising and recommendation, 5G optimization, logistics scheduling, etc.
