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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...
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| Publicado no: | Front Robot AI |
|---|---|
| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7805929/ https://ncbi.nlm.nih.gov/pubmed/33500934 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/frobt.2018.00049 |
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