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  1. Reinforcement Learning for Control Systems Applications

    You can use deep neural networks, trained using reinforcement learning, to implement such complex controllers. These systems can be self-taught without intervention from an expert …

  2. Guide to Understanding Reinforcement Learning - MATLAB

    Learn the basics of reinforcement learning and how it compares with traditional control design. Download the ebook to get started with reinforcement learning in MATLAB and Simulink.

  3. From Shortest Paths to Reinforcement Learning - Springer

    This book fills a gap between the statement of DP principles and their actual software implementation. Using MATLAB throughout, this tutorial gently gets the reader acquainted with …

  4. Solving Optimal control and Search Problems with Reinforcement Learning ...

    The following section describes my implementation of this problem and a general MATLAB environment for simulating reinforcement learning control problems and solutions. A MATLAB …

  5. Reinforcement Learning with MATLAB and Simulink

    Section 1: The Basics and Setting Up the Environment - Learn the basics of reinforcement learning and how it compares with traditional control design. See the difference between …

  6. 7 must read books for Reinforcement Learning | by ML Blogger

    Jan 8, 2023 · The following are 7 must read books on Reinforcement learning which will give you the necessary background to use RL in your work or pursue further research in this field. 1. …

  7. Optimal Control - Frank L. Lewis, Draguna Vrabie, Vassilis L.

    Mar 20, 2012 · An abundance of computer simulations using MATLAB and relevant Toolboxes is included to give the reader the actual experience of applying the theory to real-world …

  8. model-based reinforcement learning is used to solve approximate optimal control problems online under a finite excitation condition. The development is based on the observation that, given a …

  9. Textbook: Reinforcement Learning and Optimal Control - MIT

    We discuss solution methods that rely on approximations to produce suboptimal policies with adequate performance. These methods are collectively known by several essentially …

  10. Practical Reinforcement Learning for Controls: Design, Test, and ...

    Jun 29, 2022 · We introduce ideas on how to use reinforcement learning for practical control design with MATLAB and Reinforcement Learning Toolbox, using a complete workflow for the …

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