rlPredefinedEnv

Create a predefined reinforcement learning environment

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Syntax

env = rlPredefinedEnv(keyword)

Description

example

env = rlPredefinedEnv(keyword) takes a predefined keyword keyword representing the environment name to create a MATLAB® or Simulink® reinforcement learning environment env. The environment env models the dynamics with which the agent interacts, generating rewards and observations in response to agent actions.

Examples

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Open Live Script

Use the predefined 'BasicGridWorld' keyword to create a basic grid world reinforcement learning environment.

env = rlPredefinedEnv('BasicGridWorld')
env = 
  rlMDPEnv with properties:

       Model: [1x1 rl.env.GridWorld]
    ResetFcn: []
Open Live Script

Use the predefined 'DoubleIntegrator-Continuous' keyword to create a continuous double integrator reinforcement learning environment.

env = rlPredefinedEnv('DoubleIntegrator-Continuous')
env = 
  DoubleIntegratorContinuousAction with properties:

             Gain: 1
               Ts: 0.1000
      MaxDistance: 5
    GoalThreshold: 0.0100
                Q: [2x2 double]
                R: 0.0100
         MaxForce: Inf
            State: [2x1 double]

You can visualize the environment using the plot function and interact with it using the reset and step functions.

plot(env)
observation = reset(env)
observation = 2×1

     4
     0


[observation,reward,isDone] = step(env,16)

observation = 2×1

    4.0800
    1.6000


reward = -16.5559

isDone = logical
   0
Open Live Script

Use the predefined 'SimplePendulumModel-Continuous' keyword to create a continuous simple pendulum model reinforcement learning environment.

env = rlPredefinedEnv('SimplePendulumModel-Continuous')
env = 
SimulinkEnvWithAgent with properties:

           Model : rlSimplePendulumModel
      AgentBlock : rlSimplePendulumModel/RL Agent
        ResetFcn : []
  UseFastRestart : on

Input Arguments

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Predefined keyword representing the environment name, specified as one of the following:

MATLAB Environment

  • 'BasicGridWorld'

  • 'CartPole-Discrete'

  • 'CartPole-Continuous'

  • 'DoubleIntegrator-Discrete'

  • 'DoubleIntegrator-Continuous'

  • 'SimplePendulumWithImage-Discrete'

  • 'SimplePendulumWithImage-Continuous'

  • 'WaterFallGridWorld-Stochastic'

  • 'WaterFallGridWorld-Deterministic'

Simulink Environment

  • 'SimplePendulumModel-Discrete'

  • 'SimplePendulumModel-Continuous'

  • 'CartPoleSimscapeModel-Discrete'

  • 'CartPoleSimscapeModel-Continuous'

Output Arguments

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MATLAB or Simulink environment object, returned as one of the following:

  • rlMDPEnv object, when you use one of the following keywords:

    • 'BasicGridWorld'

    • 'WaterFallGridWorld-Stochastic'

    • 'WaterFallGridWorld-Deterministic'

  • CartPoleDiscreteAction object, when you use the 'CartPole-Discrete' keyword.

  • CartPoleContinuousAction object, when you use the 'CartPole-Continuous' keyword.

  • DoubleIntegratorDiscreteAction object, when you use the 'DoubleIntegrator-Discrete' keyword.

  • DoubleIntegratorContinuousAction object, when you use the 'DoubleIntegrator-Continuous' keyword.

  • SimplePendlumWithImageDiscreteAction object, when you use the 'SimplePendulumWithImage-Discrete' keyword.

  • SimplePendlumWithImageContinuousAction object, when you use the 'SimplePendulumWithImage-Continuous' keyword.

  • SimulinkEnvWithAgent object, when you use one of the following keywords:

    • 'SimplePendulumModel-Discrete'

    • 'SimplePendulumModel-Continuous'

    • 'CartPoleSimscapeModel-Discrete'

    • 'CartPoleSimscapeModel-Continuous'

See Also

Topics

Introduced in R2019a

Reinforcement Learning Toolbox Documentation

Support