134 citations · 137 across the 7 of their papers we have counts for
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cs.LG2020
Learning Task-Agnostic Action Spaces for Movement Optimization
Amin Babadi, Michiel van de Panne, C. Karen Liu +1
We propose a novel method for exploring the dynamics of physically based animated characters, and learning a task-agnostic action space that makes movement optimization easier. Lik…
cs.LG2016★ 134 cited
Learning Locomotion Skills Using DeepRL: Does the Choice of Action Space Matter?
Xue Bin Peng, Michiel van de Panne
The use of deep reinforcement learning allows for high-dimensional state descriptors, but little is known about how the choice of action representation impacts the learning difficu…