Online fitted policy iteration based on extreme learning machines
Reinforcement learning (RL) is a learning paradigm that can be useful in a wide variety of real-world applications. However, its applicability to complex problems remains problematic due to different causes. Particularly important among these are the high quantity of data required by the agent to le...
| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.11939/6972 https://www.sciencedirect.com/science/article/abs/pii/S0950705116001209#! |
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