Topics - e-Bulletin
University of Electro-Communications publishes the February 2021 issue of UEC e-Bulletin
The February 2021issue of the UEC e-Bulletin includes an informative video of a UEC researcher describing his activities on innovative control theory for control, reinforcement learning, and power systems.
Research highlights 'Innovative automated control systems: Control-theoretic approach for fast online reinforcement learning,' Tomonori Sadamoto; 'Computing in close proximity: Edge intelligence with deep reinforcement learning,' Celimuge Wu.
News and Events page is on the ‘7th UEC Seminar in ASEAN, 2020 and the 2nd ASEAN - UEC Workshop' held on November 21, 2020.
Research Highlights
Innovative automated control systems: Control-theoretic approach for fast online reinforcement learning
Reinforcement Learning (RL) is an effective way of designing model-free linear quadratic regulators (LQRs) for linear time-invariant networks with unknown state-space models. RL has wide ranging applications including industrial automation, self-driving automobiles, power grid systems, and even forecasting stock prices for financial markets.
Computing in close proximity: Edge intelligence with deep reinforcement learning
Mobile edge computing (MEC) is a promising paradigm to improve the quality of computation experience for mobile devices by providing computing capabilities in close proximity. MEC finds applications in homes, factories, and transport modes including trains and airplanes. However, the design of computation offloading policies for an MEC system, specifically, the decision of executing a computation task at the mobile device or at the remote MEC server, should adapt to the network randomness and uncertainties.
Researcher Video Profiles
Innovative control theory: Bridging the gap between research on control, reinforcement learning, and power systems
Reinforcement learning is a key methodology for controlling large-scale complex systems such as power grids and transportation networks. However, the major contemporary learning theories currently used are unsuitable for real-time control because designers must repeat trials just for acquiring data. Instead, it is necessary to develop a methodology that is capable of real-time decision making.
News and Events
UEC holds the 7th UEC Seminar in ASEAN, 2020 and the 2nd ASEAN - UEC Workshop
On November 21, 2020, the University of Electro-Communications (UEC) held the 7th UEC Seminar in ASEAN, 2020 and the 2nd ASEAN - UEC Workshop on Energy and AI online in collaboration with Bundung Institute of Technology (ITB), Indonesia, and the ECTI Association.