Introduction to Reinforcement Learning with MATLAB скачать в хорошем качестве

Introduction to Reinforcement Learning with MATLAB

Watch this video for an introduction to reinforcement learning with MATLAB and Reinforcement Learning Toolbox™. Reinforcement learning is a type of machine learning technique where a computer agent learns to perform a task through repeated trial-and-error interactions with a dynamic environment. This video introduces reinforcement learning by going through an example that trains a quadruped robot to walk with MATLAB and Reinforcement Learning Toolbox. You will learn how to: • Create a reinforcement learning environment in MATLAB and Simulink • Synthesize reward signals for training • Create neural network policies interactively or programmatically • Select and design the appropriate reinforcement learning agent • Train your agent and inspect training results • Generate C/C++ code for deploying the trained policy Learn the essentials of reinforcement learning through Reinforcement Learning Onramp: https://bit.ly/3vUw4ug Quadruped Robot Locomotion Using DDPG Agent Example: https://bit.ly/3LtYnWN Related Products: • Reinforcement Learning Toolbox: https://bit.ly/3vL1Olq • Deep Learning Toolbox: https://bit.ly/3yEX9TL • Simulink: https://bit.ly/3vPfNXy -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2022 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.