176 citations · 533 across the 49 of their papers we have counts for
3 papers · 1 filter
Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions
Alejandro Escontrela, Xue Bin Peng, Wenhao Yu +4
Training a high-dimensional simulated agent with an under-specified reward function often leads the agent to learn physically infeasible strategies that are ineffective when deploy…
A Berkeley View of Systems Challenges for AI
Ion Stoica, Dawn Song, Raluca Ada Popa +11
With the increasing commoditization of computer vision, speech recognition and machine translation systems and the widespread deployment of learning-based back-end technologies suc…
Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning
Richard Liaw, Sanjay Krishnan, Animesh Garg +3
Rather than learning new control policies for each new task, it is possible, when tasks share some structure, to compose a "meta-policy" from previously learned policies. This pape…