rlPredefinedEnv
Create a predefined reinforcement learning environment
Description
takes a predefined keyword env = rlPredefinedEnv(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
Input Arguments
Output Arguments
Version History
Introduced in R2019a
See Also
Functions
getObservationInfo|getActionInfo|train|sim|rlCreateEnvTemplate|rlSimulinkEnv|createIntegratedEnv
Objects
rlNumericSpec|rlFiniteSetSpec|rlMDPEnv|rlFunctionEnv|rlMultiAgentFunctionEnv|rlTurnBasedFunctionEnv|SimulinkEnvWithAgent
Topics
- Train Reinforcement Learning Agent in Basic Grid World
- Train Default DQN Agent to Balance Discrete Cart-Pole
- Train Default DDPG Agent to Swing Up and Balance Continuous Pendulum
- Reinforcement Learning Environments
- Create Custom Simulink Environments
- Use Predefined Grid World Environments
- Use Predefined Control System Environments
