Getting Started with Reinforcement Learning
Get started with reinforcement learning and Reinforcement Learning Toolbox™ by walking through an example that trains a quadruped robot to walk. This video covers the basics of reinforcement learning and gives you an idea of what it is like to work with 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.
Watch this video to learn how Reinforcement Learning Toolbox helps you:
• Create a reinforcement learning environment in 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/37LISv3
• Simulink: https://bit.ly/3vPfNXy
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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.
Get started with reinforcement learning and Reinforcement Learning Toolbox™ by walking through an example that trains a quadruped robot to walk. This video covers the basics of reinforcement learning and gives you an idea of what it is like to work with 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.
Watch this video to learn how Reinforcement Learning Toolbox helps you:
• Create a reinforcement learning environment in 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/37LISv3
• Simulink: https://bit.ly/3vPfNXy
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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.
