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Our work, "A Primer on SO(3) Action Representations in Deep Reinforcement Learning," was accepted to #ICLR2026! We provide a systematic study of action representation choices in RL, showing that they fundamentally impact training stability and performance. #Robotics #AI #RL

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Learning Systems and Robotics Lab (is hiring!)

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49,655 просмотров • 4 месяцев назад •via X (Twitter)

Наука и технологии#ICLR2026#Robotics#AI#RL
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Deployment-Ready RL: Pitfalls, Lessons, and Best Practices We’ve published a full transcript of a webinar with Kyle🤖🚀🦭 (UT Austin) and the Humanoid team on our blog. He explores Sim2Real RL: - Action Space - Observation Space - Dealing with Model Mismatch - Reward Tuning Intuition - RL with Motion References We’re sharing this to spread knowledge & help push humanoid robotics forward. Read or listen here:

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