ELEC-E8125 - Reinforcement learning D, Lecture, 5.9.2022-30.11.2022

Resources

• Resources
  

  Resources

  This section includes useful resources that are helpful for finishing assignments, understanding reinforcement learning, and doing research.

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    FolderPyTorch Tutorial Folder
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    URLPython, Numpy Tutorial URL
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    URLPyTorch Official Tutorial URL
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    URLDive into Deep Learning URL
  • Readings and other materials
    

    Mark as done
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    URLSutton & Barto, Reinforcement Learning: An introduction, 2nd ed. URL

    Mark as done
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    URLPlatt, Introduction to Linear Quadratic Regulation URL

    Mark as done
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    URLReinforcement learning course at UCL URL
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    URLDeep reinforcement learning course at UC Berkeley URL
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    URLLaValle, Planning Algorithms URL

    Mark as done
  • Extra links
    

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    URLModel-based reinforcement learning tutorial (ICML 2020) URL
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    URLBradberry, "Introduction to Monte Carlo Tree Search" URL
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    URLDeep Reinforcement Learning: Pong from Pixels URL
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    URLAlphaGo: using machine learning to master the ancient game of Go URL
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    URLAndrew Ng, "Nuts and Bolts of Applying Deep Learning" (video) URL