What is the difference between model-free and model-based reinforcement learning? Does training against a simulation model require model-based reinforcement learning? What if you don’t have a model available? Explore the differences and results as the learning models are applied to balancing a cart/pole system as an example. By the end, you will have a better understanding of situations where you may want to choose model-based reinforcement learning. MATLAB Example: Train MBPO Agent to Balance Cart-Pole System: Watch this video to see how to apply model-based reinforcement learning with Reinforcement Learning Toolbox: Watch our full video series about Reinforcement Learning: By the end of this series, you’ll be better prepared to answer questions like: - What is reinforcement learning and why should I consider it when solving my control problem? - How do I set up and solve the reinforcement learning problem? - What are some of the benefits and drawbacks of reinforcement learning compared to a traditional controls approach? Artificial intelligence, machine learning, deep neural networks. These are terms that can spark your imagination of a future where robots are thinking and evolving creatures. Check out these other resources: - Reinforcement Learning by Sutton and Barto: - Reinforcement Learning Course by David Silver: - Reinforcement Learning Toolbox: - Deep Reinforcement Learning for Walking Robots: Check out the individual videos in the series: • What Is Reinforcement Learning?: • Understanding the Environment and Rewards: • Policies and Learning Algorithms: • The Walking Robot Problem: • Overcoming the Practical Challenges: • An Introduction to Multi-Agent Reinforcement Learning: • Why Choose Model-Based Reinforcement Learning?: 0:00 Introduction 0:28 What is model-free reinforcement learning? 1:13 What is model-based reinforcement learning? 1:44 A sports analogy of model-free vs model-based reinforcement learning 3:25 Real vs simulated experiences 4:59 Using simulation environments does not imply model-based reinforcement learning 5:50 Why choose model-free reinforcement learning? 6:50 Why choose model-based reinforcement learning? 8:29 What if you don’t have a model? 10:25 Learning an ensemble of models 12:54 Model-based reinforcement learning example in MATLAB -------------------------------------------------------------------------------------------------------- Get a free product trial: Learn more about MATLAB: Learn more about Simulink: See what's new in MATLAB and Simulink: © 2022 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.