Yulun Li
Engineering Blog Articles
Creating a Zoo of Atari-Playing Agents to Catalyze the Understanding of Deep Reinforcement Learning
Uber AI Labs releases Atari Model Zoo, an open source repository of both trained Atari Learning Environment agents and tools to better understand them.
Research Papers
An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents
F. Such, V. Madhavan, R. Liu, R. Wang, P. Castro, Y. Li, L. Schubert, M. Bellemare, J. Clune, J. Lehman
Much human and computational effort has aimed to improve how deep reinforcement learning algorithms perform on benchmarks such as the Atari Learning Environment. Comparatively less effort has focused on understanding what has been learned by such methods, and investigating and comparing the representations learned by different families of reinforcement learning (RL) algorithms. [...] [PDF at arXiv]
2019
Much human and computational effort has aimed to improve how deep reinforcement learning algorithms perform on benchmarks such as the Atari Learning Environment. Comparatively less effort has focused on understanding what has been learned by such methods, and investigating and comparing the representations learned by different families of reinforcement learning (RL) algorithms. [...] [PDF at arXiv]
2019
