Reinforcement-Learning-RL-with-MATLAB

版本 1.0.0 (23.1 MB) 作者: Mohammad Dehghani
This repository contains series of modules to get started with Reinforcement Learning with MATLAB.
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Reinforcement-Learning-RL-with-MATLAB

This repository contains series of modules to get started with Reinforcement Learning with MATLAB.

Solutions are available upon instructor request. Please contact HERE

It is divided into 4 stages.

In Stage 1 we start with learning RL concepts by manually coding the RL problem. Later we see how the same thing can be done by using functions available in MathWorks RL toolbox.

In Stage 2, we deal with complex environments and learn how Deep Learning agents are modelled and trained. Additionally, we see how to custom build an environment in MATLAB.

In Stage 3 we introduce Simulink. We develop environments using Simulink RL blocks.

In Stage 4 brings us to additional environments of Mechanical and Industrial Engineering problems, that we will build using the concepts taught before.

Please go through the folder named 'Introduction and Documentation' to get started with the modules. You can view the MATLAB script by opening the PDF associated with that repective module.

Citation: Sahil S. Belsare, Mohammad Dehghani, Rifat Sipahi, (2022). Reinforcement-Learning-RL-with-MATLAB (https://github.com/mdehghani86/Reinforcement-Learning-RL-with-MATLAB/releases/tag/v1.0.0), GitHub. Retrieved May 10, 2022.

引用格式

Sahil S. Belsare, Mohammad Dehghani, Rifat Sipahi, (2022). Reinforcement-Learning-RL-with-MATLAB (https://github.com/mdehghani86/Reinforcement-Learning-RL-with-MATLAB/releases/tag/v1.0.0), GitHub. Retrieved May 10, 2022.

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2- Stage 2 - RL with Deep Learning Agents/01- Custom Cart Pole_ DQN

3- Stage 3 - Simulink and RL

4 - Stage 4 - Additional Engineering Environments/Robot Walk Using ReinforcementLearning

3- Stage 3 - Simulink and RL

4 - Stage 4 - Additional Engineering Environments/Robot Walk Using ReinforcementLearning

1- Stage_1 Solving an MDP with an Q_learning agent/1 - Simple MDP with Qlearning Agent_Manual

1- Stage_1 Solving an MDP with an Q_learning agent/2 - Simple MDP with Qlearning Agent_MATLAB

2- Stage 2 - RL with Deep Learning Agents/00- Stochastic Gridworld_DQN

2- Stage 2 - RL with Deep Learning Agents/01- Custom Cart Pole_ DQN

3- Stage 3 - Simulink and RL

4 - Stage 4 - Additional Engineering Environments/Portfolio Management Using Reinforcement Learning

4 - Stage 4 - Additional Engineering Environments/Robot Walk Using ReinforcementLearning

版本 已发布 发行说明
1.0.0

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