Bootstrapping of Parameterized Skills Through Hybrid Optimization in Task and Policy Spaces
Modern robotic applications create high demands on adaptation of actions with respect to variance in a given task. Reinforcement learning is able to optimize for these changing conditions, but relearning from scratch is hardly feasible due to the high number of required rollouts. We propose a parame...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2018-06-01
|
Series: | Frontiers in Robotics and AI |
Subjects: | |
Online Access: | https://www.frontiersin.org/article/10.3389/frobt.2018.00049/full |