UofT-Developed RL System Drives Cost Down for Robotics Research

Image credit: OpenAI
Image credit: A. Allshire, M. Mittal, et al
  1. Allshire, A., Mittal, M., Lodaya, V., & Makoviychuk, V. (2021, August 22). Transferring dexterous manipulation from GPU Simulation to a Remote Real-World TriFinger. arxiv.org. Retrieved October 10, 2021, from https://arxiv.org/pdf/2108.09779.pdf.
  2. Dickson, B. (2021, September 27). Nvidia, University of Toronto are making robotics research available to small firms. TechTalks. Retrieved October 7, 2021, from https://bdtechtalks.com/2021/09/27/nvidia-robotic-hand-simulation-training/.
  3. Negrello, F., Stuart, H. S., & Catalano, M. G. (1AD, January 1). Hands in the real world. Frontiers. Retrieved October 7, 2021, from https://www.frontiersin.org/articles/10.3389/frobt.2019.00147/full.
  4. Schulman, J. (2020, September 2). Proximal policy optimization. OpenAI. Retrieved October 7, 2021, from https://openai.com/blog/openai-baselines-ppo/.

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University of Toronto Machine Intelligence Team

University of Toronto Machine Intelligence Team

UTMIST’s Technical Writing Team publishes articles on topics within machine learning to our official publication: https://medium.com/demistify