no code implementations • 23 Feb 2024 • Zihan Zhou, Jonathan Booher, Khashayar Rohanimanesh, Wei Liu, Aleksandr Petiushko, Animesh Garg
Safe reinforcement learning tasks with multiple constraints are a challenging domain despite being very common in the real world.
no code implementations • 11 Nov 2019 • Ajay Mandlekar, Jonathan Booher, Max Spero, Albert Tung, Anchit Gupta, Yuke Zhu, Animesh Garg, Silvio Savarese, Li Fei-Fei
We evaluate the quality of our platform, the diversity of demonstrations in our dataset, and the utility of our dataset via quantitative and qualitative analysis.
no code implementations • 7 Nov 2018 • Ajay Mandlekar, Yuke Zhu, Animesh Garg, Jonathan Booher, Max Spero, Albert Tung, Julian Gao, John Emmons, Anchit Gupta, Emre Orbay, Silvio Savarese, Li Fei-Fei
Imitation Learning has empowered recent advances in learning robotic manipulation tasks by addressing shortcomings of Reinforcement Learning such as exploration and reward specification.