| Title | : | Recent Advances of Deep Reinforcement Learning |
| Speaker | : | Dr. Thanh Thi Nguyen (Deakin University) |
| Details | : | Wed, 26 Feb, 2020 12:00 PM @ AM Turing Hall |
| Abstract: | : | Deep learning has enabled traditional reinforcement learning methods to deal with high-dimensional problems. However, there have been several issues with deep reinforcement learning methods such as the limited exploration capability of learning agents, the ability to integrate human knowledge into learning agents or their extendibility to handle multi-objective problems as well as multi-agent control. In this talk, I will discuss these issues and present my recent studies on deep reinforcement learning to address these issues. Bio:Thanh Thi Nguyen was a Visiting Scholar with the Computer Science Department at Stanford University, California, USA in 2015 and the Edge Computing Lab, John A. Paulson School of Engineering and Applied Sciences, Harvard University, Massachusetts, USA in 2019. He received an Alfred Deakin Postdoctoral Research Fellowship in 2016, a European-Pacific Partnership for ICT Expert Exchange Program Award from European Commission in 2018, and an Australia–India Strategic Research Fund Early- and Mid-Career Fellowship Awarded by The Australian Academy of Science in 2020. Dr. Nguyen obtained a PhD in Mathematics and Statistics from Monash University, Australia in 2013 and has expertise in various areas, including artificial intelligence, deep learning, deep reinforcement learning, cyber security, IoT, and data science. He is currently a Senior Lecturer in the School of Information Technology, Deakin University, Victoria, Australia. |
