- Design your Simulink model to represent the environment. This model should have inputs for actions and outputs for observations and rewards.
- Use MATLAB to implement your RL algorithm. You can use custom scripts or functions to define the learning process, policy updates, and action selection. For instance, a script that takes observations, rewards and isDone parameters as input and outputs the action taken by the agent.
- Use the MATLAB Function block or S-Function block to interface your RL algorithm with the Simulink model. This block will handle the communication between the Simulink model and the MATLAB workspace.
matlab reinforcement learning module RL Agent
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I would like to ask how to use the agent module in simulink for the matlab version before 2020, because the version before 2020 does not have RL agent encapsulation
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Ayush Aniket
2024-9-16
One way you can implement reinforcement learning in Simulink without using a RL Agent block can be by following these steps:
Refer the following documentation links to read about an example of creating a custom agent and MATLAB Function block:
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