What Is Reinforcement Learning?
96.4 هزار بار بازدید -
5 سال پیش
-
In this video, we provide
In this video, we provide an overview of reinforcement learning from the perspective of an engineer. Reinforcement learning is type of machine learning that has the potential to solve some really hard control problems.
Watch our full video series about Reinforcement Learning: 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: http://bit.ly/2HAYbb4
Reinforcement Learning Course by David Silver: RL Course by David Silver - Lecture 1...
Reinforcement Learning Toolbox: https://bit.ly/2YjuAYa
Deep Reinforcement Learning for Walking Robots: Deep Reinforcement Learning for Walki...
Check out the individual videos in the series:
• What Is Reinforcement Learning?: What Is Reinforcement Learning?
• Understanding the Environment and Rewards: Understanding Reinforcement Learning ...
• Policies and Learning Algorithms: Reinforcement Learning Policies and L...
• The Walking Robot Problem: Solving the Walking Robot Problem wit...
• Overcoming the Practical Challenges: Overcoming the Practical Challenges w...
• An Introduction to Multi-Agent Reinforcement Learning: Introduction to Multi-Agent Reinforce...
• Why Choose Model-Based Reinforcement Learning?: Why Choose Model-Based Reinforcement ...
Chapters:
00:00 – Introduction
00:16 – what is reinforcement learning?
03:00 – how does unsupervised learning work?
03:32 – how does supervised learning work?
05:13 – Reinforcement learning environment
05:28 - RL agent
05:58 – RL reward
06:37 – Reinforcement learning policy
07:39 – Reinforcement learning algorithms
09:58 – Exploration vs. exploitation
11:10 Analogies with traditional control design
12:25 – What to consider before formulating an RL problem
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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.
Watch our full video series about Reinforcement Learning: 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: http://bit.ly/2HAYbb4
Reinforcement Learning Course by David Silver: RL Course by David Silver - Lecture 1...
Reinforcement Learning Toolbox: https://bit.ly/2YjuAYa
Deep Reinforcement Learning for Walking Robots: Deep Reinforcement Learning for Walki...
Check out the individual videos in the series:
• What Is Reinforcement Learning?: What Is Reinforcement Learning?
• Understanding the Environment and Rewards: Understanding Reinforcement Learning ...
• Policies and Learning Algorithms: Reinforcement Learning Policies and L...
• The Walking Robot Problem: Solving the Walking Robot Problem wit...
• Overcoming the Practical Challenges: Overcoming the Practical Challenges w...
• An Introduction to Multi-Agent Reinforcement Learning: Introduction to Multi-Agent Reinforce...
• Why Choose Model-Based Reinforcement Learning?: Why Choose Model-Based Reinforcement ...
Chapters:
00:00 – Introduction
00:16 – what is reinforcement learning?
03:00 – how does unsupervised learning work?
03:32 – how does supervised learning work?
05:13 – Reinforcement learning environment
05:28 - RL agent
05:58 – RL reward
06:37 – Reinforcement learning policy
07:39 – Reinforcement learning algorithms
09:58 – Exploration vs. exploitation
11:10 Analogies with traditional control design
12:25 – What to consider before formulating an RL problem
--------------------------------------------------------------------------------------------------------
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.
5 سال پیش
در تاریخ 1398/01/05 منتشر شده
است.
96,457
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