[图书][B] Reinforcement learning for robots using neural networks
LJ Lin - 1992 - search.proquest.com
Reinforcement learning agents are adaptive, reactive, and self-supervised. The aim of this
dissertation is to extend the state of the art of reinforcement learning and enable its …
dissertation is to extend the state of the art of reinforcement learning and enable its …
[引用][C] Reinforcement learning for robots using neural networks
LJ LIN - PhD thesis, Carnegie Mellon University, Pittsburgh, 1993 - cir.nii.ac.jp
Reinforcement Learning for Robots Using Neural Networks
LJ Lin - 1993 - apps.dtic.mil
Reinforcement learning agents are adaptive, reactive, and self-supervised. The aim of this
dissertation is to extend the state of the art of reinforcement learning and enable its …
dissertation is to extend the state of the art of reinforcement learning and enable its …
Reinforcement learning for robots using neural networks
LJ Lin - 1992 - dl.acm.org
Reinforcement learning agents are adaptive, reactive, and self-supervised. The aim of this
dissertation is to extend the state of the art of reinforcement learning and enable its …
dissertation is to extend the state of the art of reinforcement learning and enable its …
[引用][C] Reinforcement learning for robots using neural networks
LJ LIN - PhD thesis, Carnegie Mellon University, 1992 - cir.nii.ac.jp
[PDF][PDF] Reinforcement Learning for Robots Using Neural Networks
LJ Lin - 1993 - apps.dtic.mil
Reinforcement learning agents are adaptive, reactive, and self-supervised. The aim of this
dissertation is to extend the state of the art of reinforcement learning and enable its …
dissertation is to extend the state of the art of reinforcement learning and enable its …