rlNumericSpec
Create continuous action or observation data specifications for reinforcement learning environments
Description
An rlNumericSpec
object specifies continuous action or
observation data specifications for reinforcement learning environments.
Creation
Description
creates a data specification for continuous actions or observations and sets the Dimension
property.spec
= rlNumericSpec(dimension
)
sets Properties using name-value pair
arguments.spec
= rlNumericSpec(dimension
,Name,Value
)
Properties
Object Functions
rlSimulinkEnv | Create reinforcement learning environment using dynamic model implemented in Simulink |
rlFunctionEnv | Specify custom reinforcement learning environment dynamics using functions |
rlValueFunction | Value function approximator object for reinforcement learning agents |
rlQValueFunction | Q-Value function approximator object for reinforcement learning agents |
rlVectorQValueFunction | Vector Q-value function approximator for reinforcement learning agents |
rlContinuousDeterministicActor | Deterministic actor with a continuous action space for reinforcement learning agents |
rlDiscreteCategoricalActor | Stochastic categorical actor with a discrete action space for reinforcement learning agents |
rlContinuousGaussianActor | Stochastic Gaussian actor with a continuous action space for reinforcement learning agents |
Examples
Version History
Introduced in R2019a