public interface ReinforcementLearningModel<ROOT extends Agent,O,A,C>
Modifier and Type | Method and Description |
---|---|
void |
applyAction(ROOT root,
A action)
This method must be defined in a subclass to get the data from the given
action object and
apply it to the model (root ). |
void |
applyConfiguration(ROOT root,
C configuration)
This method must be defined in a subclass to get the data from the given
configuration object and
apply it as the initial setup to the model (root ). |
boolean |
checkEpisodeStopCondition(ROOT root)
This method may be defined in a subclass to check the additional stop condition of the Episode.
|
A |
createAction()
This method must be defined in a subclass - just to create new empty Action object
|
C |
createConfiguration()
This method must be defined in a subclass - just to create new empty Configuration object
|
ROOT |
createModel()
Is called to obtain a new pre-initialized top-level agent.
|
O |
createObservation()
This method must be defined in a subclass - just to create new empty Observation object
|
void |
getObservation(ROOT root,
O observation)
This method must be defined in a subclass to get the data from
root and write it to the fields of the given observation . |
ROOT createModel()
engine
- the simulation engine that will simulate the modelO createObservation()
A createAction()
C createConfiguration()
void getObservation(ROOT root, O observation)
root
and write it to the fields of the given observation
.root
- the root model agentobservation
- data structure, to be filled from the simulation model and then sent to the Learning Agent (AI)void applyAction(ROOT root, A action)
action
object and
apply it to the model (root
).root
- the root model agentaction
- data structure, coming from the Learning Agent (AI) and then applied to the modelvoid applyConfiguration(ROOT root, C configuration)
configuration
object and
apply it as the initial setup to the model (root
).root
- the root model agentaction
- data structure, coming from the Reinforcement Learning platform and then applied to the modelboolean checkEpisodeStopCondition(ROOT root)
true
to request stopping the Episode (e.g. when the model falls into some
undesired terminal state which doesn't allow further training or testing of Learning Agent).true
to stop the model, false
to continue learning/simulation loopCopyright © AnyLogic North America, LLC. All Rights Reserved.