Reinforcement Learning Onramp

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Reinforcement Learning Onramp provided by MATLAB Academy is a comprehensive online course, which lasts for 3 hours worth of material. Reinforcement Learning Onramp is taught by Matt Tearle. Upon completion of the course, you can receive an e-certificate from MATLAB Academy. The course is taught in Englishand is Free Certificate. Visit the course page at MATLAB Academy for detailed price information.

MathWorks via MATLAB Academy

3 hours worth of material

Self Paced

- Overview of Reinforcement Learning: Familiarize yourself with reinforcement learning concepts and the course.
- Defining the Environment: Define how an agent interacts with an environment model.
- Defining Agents: Create representations of RL agents.
- Training Agents: Use simulation episodes to train an agent.
- Conclusion: Learn next steps and give feedback on the course.

Syllabus

- What is Reinforcement Learning
- Simulating with a Pretrained Agent
- Components of a Reinforcement Learning Model
- Defining an Environment Interface
- Providing Rewards
- Including Actions in the Reward
- Connecting a Simulink Environment to a MATLAB Agent
- Critics and Q Values
- Representing Critics for Continuous Problems
- Creating Neural Networks
- Creating Networks for Agents
- Actors and Critics
- Creating Default Agent Representations
- Summary of Agents
- Training
- Changing Options
- Improving Training
- Summary of Functions
- Additional Resources
- Survey

5, based on 1 Course votes at GetYourEducation

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Language

English
Certificate
Certificate Available
Date of Start
30th December, 2022
Price
Free Certificate
Provider
MATLAB Academy
Taught By

Matt Tearle
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Reinforcement Learning Onramp

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