most citedMap-based Multi-Policy Reinforcement Learning: Enhancing Adaptability of Robots by Deep Reinforcement Learning

10 citations · 10 across the 1 of their papers we have counts for

collaborators

1 paper

cs.RO2017★ 10 cited

Map-based Multi-Policy Reinforcement Learning: Enhancing Adaptability of Robots by Deep Reinforcement Learning

Ayaka Kume, Eiichi Matsumoto, Kuniyuki Takahashi +2

In order for robots to perform mission-critical tasks, it is essential that they are able to quickly adapt to changes in their environment as well as to injuries and or other bodil…