TY - JOUR
T1 - Optimization for Reinforcement Learning
T2 - From a single agent to cooperative agents
AU - Lee, Donghwan
AU - He, Niao
AU - Kamalaruban, Parameswaran
AU - Cevher, Volkan
N1 - Funding Information:
Niao He (niaohe@illinois.edu) received her B.S. degree in mathematics from the University of Science and Technology of China in 2010 and her Ph.D. degree in operations research from the Georgia Institute of Technology, Atlanta, in 2015. Currently, she is an assistant professor in the Department of Industrial and Enterprise Systems Engineering and Coordinated Science Laboratory at the University of Illinois at Urbana–Champaign. Her research interests include optimization and machine learning. She is also a recipient of the 2016 Artificial Intelligence and Statistics (AISTATS) Best Paper Award, NSF CISE CRII Award in 2018, and National Center for Supercomputing Applications Faculty Fellowship in 2018.
Publisher Copyright:
© 1991-2012 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - Fueled by recent advances in deep neural networks, reinforcement learning (RL) has been in the limelight because of many recent breakthroughs in artificial intelligence, including defeating humans in games (e.g., chess, Go, StarCraft), self-driving cars, smart-home automation, and service robots, among many others. Despite these remarkable achievements, many basic tasks can still elude a single RL agent. Examples abound, from multiplayer games, multirobots, cellular-Antenna tilt control, traffic-control systems, and smart power grids to network management.
AB - Fueled by recent advances in deep neural networks, reinforcement learning (RL) has been in the limelight because of many recent breakthroughs in artificial intelligence, including defeating humans in games (e.g., chess, Go, StarCraft), self-driving cars, smart-home automation, and service robots, among many others. Despite these remarkable achievements, many basic tasks can still elude a single RL agent. Examples abound, from multiplayer games, multirobots, cellular-Antenna tilt control, traffic-control systems, and smart power grids to network management.
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U2 - 10.1109/MSP.2020.2976000
DO - 10.1109/MSP.2020.2976000
M3 - Article
AN - SCOPUS:85084554989
VL - 37
SP - 123
EP - 135
JO - IEEE Signal Processing Magazine
JF - IEEE Signal Processing Magazine
SN - 1053-5888
IS - 3
M1 - 9084325
ER -