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Learning to reach by reinforcement learning using a receptive field based function approximation approach with continuous actions
Reinforcement learning methods can be used in robotics applications especially for specific target-oriented problems, for example the reward-based recalibration of goal directed actions. To this end still relatively large and continuous state-action spaces need to be efficiently handled. The goal of...
| Autores principales: | , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
Springer-Verlag
2009
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2798030/ https://www.ncbi.nlm.nih.gov/pubmed/19229556 http://dx.doi.org/10.1007/s00422-009-0295-8 |