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Intelligent Control of a Sensor-Actuator System via Kernelized Least-Squares Policy Iteration
In this paper a new framework, called Compressive Kernelized Reinforcement Learning (CKRL), for computing near-optimal policies in sequential decision making with uncertainty is proposed via incorporating the non-adaptive data-independent Random Projections and nonparametric Kernelized Least-squares...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Molecular Diversity Preservation International (MDPI)
2012
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3376585/ https://www.ncbi.nlm.nih.gov/pubmed/22736969 http://dx.doi.org/10.3390/s120302632 |