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I Lee

2 accepted papers

2024

Gradient-based Regularization for Action Smoothness in Robotic Control with Reinforcement Learning

IROS 2024poster

Deep Reinforcement Learning (DRL) has achieved remarkable success, ranging from complex computer games to real-world applications, showing the potential for intelligent agents capable of learning in dynamic environments. However, its application in real-world scenarios presents challenges, including…

Cited by 0SourceScholar
2023

Image-based Regularization for Action Smoothness in Autonomous Miniature Racing Car with Deep Reinforcement Learning

IROS 2023poster

Deep reinforcement learning has achieved signif-icant results in low-level controlling tasks. However, for some applications like autonomous driving and drone flying, it is difficult to control behavior stably since the agent may suddenly change its actions which often lowers the controlling sys-tem…

Cited by 3SourceScholar