Understanding Reinforcement Learning Environment and Rewards
In this video, we build on our basic understanding of reinforcement learning by exploring the workflow. We cover what an environment is and some of the benefits of training within a simulated environment.
We cover what we ultimately want our agent to do and how crafting a reward function incentivizes the agent to do just that. And lastly, we introduce the need to choose a way to represent a policy—how we want to structure the parameters and logic that make up the decision-making part of the agent.
Watch our full video series about Reinforcement Learning: https://youtube.com/playlist?list=PLn8PRpmsu08qw_IwpgVNsKiJQpvvW0MmM
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?
Check out these other resources!
- Reinforcement Learning by Sutton and Barto: http://bit.ly/2HAYbb4
- Reinforcement Learning Course by David Silver: https://youtu.be/2pWv7GOvuf0
- Reinforcement Learning Toolbox: https://bit.ly/2YjuAYa
- Deep Reinforcement Learning for Walking Robots: https://www.youtube.com/watch?v=6DL5M9b2j6I
Check out the individual videos in the series:
• What Is Reinforcement Learning?: https://youtu.be/pc-H4vyg2L4
• Understanding the Environment and Rewards: https://youtu.be/0ODB_DvMiDI
• Policies and Learning Algorithms: https://youtu.be/7cF3VzP5EDI
• The Walking Robot Problem: https://youtu.be/Wypc1a-1ZYA
• Overcoming the Practical Challenges: https://youtu.be/zHV3UcH-nr0
• An Introduction to Multi-Agent Reinforcement Learning: https://youtu.be/qgb0gyrpiGk
• Why Choose Model-Based Reinforcement Learning?: https://youtu.be/ztT2ZLWTfXw
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© 2019 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.
In this video, we build on our basic understanding of reinforcement learning by exploring the workflow. We cover what an environment is and some of the benefits of training within a simulated environment.
We cover what we ultimately want our agent to do and how crafting a reward function incentivizes the agent to do just that. And lastly, we introduce the need to choose a way to represent a policy—how we want to structure the parameters and logic that make up the decision-making part of the agent.
Watch our full video series about Reinforcement Learning: https://youtube.com/playlist?list=PLn8PRpmsu08qw_IwpgVNsKiJQpvvW0MmM
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?
Check out these other resources!
– Reinforcement Learning by Sutton and Barto: http://bit.ly/2HAYbb4
– Reinforcement Learning Course by David Silver: https://youtu.be/2pWv7GOvuf0
– Reinforcement Learning Toolbox: https://bit.ly/2YjuAYa
– Deep Reinforcement Learning for Walking Robots: https://www.youtube.com/watch?v=6DL5M9b2j6I
Check out the individual videos in the series:
• What Is Reinforcement Learning?: https://youtu.be/pc-H4vyg2L4
• Understanding the Environment and Rewards: https://youtu.be/0ODB_DvMiDI
• Policies and Learning Algorithms: https://youtu.be/7cF3VzP5EDI
• The Walking Robot Problem: https://youtu.be/Wypc1a-1ZYA
• Overcoming the Practical Challenges: https://youtu.be/zHV3UcH-nr0
• An Introduction to Multi-Agent Reinforcement Learning: https://youtu.be/qgb0gyrpiGk
• Why Choose Model-Based Reinforcement Learning?: https://youtu.be/ztT2ZLWTfXw
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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
© 2019 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.
