Design, train, and simulate reinforcement learning agents
The Reinforcement Learning Designer app lets you design, train, and simulate agents for existing reinforcement learning environments.
Using this app, you can:
Import an existing environment from the MATLAB® workspace or create a predefined environment.
Automatically create or import an agent for your environment (DQN, DDPG, PPO, and TD3 agents are supported).
Train and simulate the agent against the environment.
Analyze simulation results and refine your agent parameters.
Export the final agent to the MATLAB workspace for further use and deployment.
The following features are not supported in the Reinforcement Learning Designer app.
Q, SARSA, PG, AC, and SAC agents
Agents relying on table or custom basis function representations
If your application requires any of these features then design, train, and simulate your agent at the command line.
MATLAB Toolstrip: On the Apps tab, under Machine Learning and Deep Learning, click the app icon.
MATLAB command prompt: Enter
reinforcementLearningDesigner opens the Reinforcement Learning
Designer app. You can then import an environment and start the design process, or
open a saved design session.