MATLAB and Simulink Training

Course Details

This one-day course introduces reinforcement learning in the MATLAB® and Simulink® environments, focusing on using the Reinforcement Learning Toolbox™.

Topics include:

  • Environment and Rewards
  • Policy and Agent
  • Neural Networks and Training
  • Deployment

Day 1 of 1


Environment and Rewards

Objective: Set up an environment and shape rewards in Simulink or MATLAB.

  • Set up environment in Simulink
  • Write a reward function
  • Set up an agent using Simulink and MATLAB
  • Connect agent and environment

Policy and Agent

Objective: Create an policy representation and construct an agent.

  • Represent a policy with a neural network
  • Create a reinforcement learning agent in MATLAB
  • Specify simulation options to run a simulation

Neural Networks and Training

Objective: Assemble a neural network for a policy representation and train an agent.

  • Assemble a neural network
  • Deep Network Designer app
  • Training an agent
  • Reinforcement Learning Designer app

Deployment

Objective: Generate code from a trained agent.

  • Generate code
  • Validation of code

Level: Intermediate

Duration: 1 day

Languages: English, 한국어