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research article
Optimization for Reinforcement Learning: From a single agent to cooperative agents
May 1, 2020
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.
Type
research article
Web of Science ID
WOS:000532218500015
Authors
Publication date
2020-05-01
Published in
Volume
37
Issue
3
Start page
123
End page
135
Peer reviewed
REVIEWED
EPFL units
Available on Infoscience
May 28, 2020
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