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design, train, and simulate reinforcement learning agents -凯发k8网页登录

design, train, and simulate reinforcement learning agents

since r2021a

description

the reinforcement learning designer app lets you design, train, and simulate agents for existing 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, td3, sac, and ppo 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.

limitations

the following features are not supported in the reinforcement learning designer app.

  • multi-agent systems

  • q, sarsa, pg, ac, and sac agents

  • custom 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.

open the reinforcement learning designer app

  • matlab toolstrip: on the apps tab, under machine learning and deep learning, click the app icon.

  • matlab command prompt: enter reinforcementlearningdesigner.

examples

programmatic use

reinforcementlearningdesigner opens the reinforcement learning designer app. you can then import an environment and start the design process, or open a saved design session.

version history

introduced in r2021a

see also

apps

functions

objects

topics

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