rlMDPEnv
Create Markov decision process environment for reinforcement learning
Description
A Markov decision process (MDP) is a discrete time stochastic control process. It
provides a mathematical framework for modeling decision making in situations where outcomes
are partly random and partly under the control of the decision maker. MDPs are useful for
studying optimization problems solved using reinforcement learning. Use
rlMDPEnv
to create a Markov decision process environment for
reinforcement learning in MATLAB®.
Creation
Syntax
Description
Input Arguments
Properties
Object Functions
getActionInfo | Obtain action data specifications from reinforcement learning environment, agent, or experience buffer |
getObservationInfo | Obtain observation data specifications from reinforcement learning environment, agent, or experience buffer |
sim | Simulate trained reinforcement learning agents within specified environment |
train | Train reinforcement learning agents within a specified environment |
validateEnvironment | Validate custom reinforcement learning environment |
Examples
Version History
Introduced in R2019a