|
||||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Objectedu.iastate.jrelm.rl.AbstractStatlessLearner<GBMParameters,I,A,Feedback<java.lang.Double>,SimpleStatelessPolicy<I,A>>
edu.iastate.jrelm.rl.bushmosteller.GBMLearner<I,A>
I
- A
- public class GBMLearner<I,A extends Action<I>>
An implementation of the Generalized Bush-Mosteller reinforcement learning module.
Constructor Summary | |
---|---|
GBMLearner(GBMParameters learningParams,
SimpleStatelessPolicy<I,A> aPolicy)
|
Method Summary | |
---|---|
java.lang.String |
getName()
Retrieves the name of the learning algorithm this learner implements. |
GBMParameters |
getParameters()
Retrieve the RLParameters that contain settings for this learning algorithm. |
SimpleStatelessPolicy<I,A> |
getPolicy()
Retrieve the StatelessPolicy being used to represent learned knowledge. |
GBMParameters |
makeParameters()
The implementation of Generalised Bush-Mosteller learning is partially distributed between the GBMLearnerTest and a specific child of GBMParameters. |
void |
setParameters(GBMParameters params)
Note, this method will check that these parameters are valid before accepting them (PA.validate()). |
void |
setPolicy(SimpleStatelessPolicy<I,A> newPolicy)
Set the StatelessPolicy to be used to represent learned knowledge. |
void |
update(Feedback<java.lang.Double> reward)
Implements the core learning function according to the Generalised Bush-Mosteller model. |
Methods inherited from class edu.iastate.jrelm.rl.AbstractStatlessLearner |
---|
chooseAction, getLastRandSeed, getLastSelectedAction, getUpdateCount, incrementUpdateCount, init, resetUpdateCount, setLastRandSeed, setLastSelectedAction, setUpdateCount |
Methods inherited from class java.lang.Object |
---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
---|
public GBMLearner(GBMParameters learningParams, SimpleStatelessPolicy<I,A> aPolicy)
Method Detail |
---|
public void update(Feedback<java.lang.Double> reward)
reward
- - feedback for the specified actionpublic GBMParameters getParameters()
ReinforcementLearner
getParameters
in interface ReinforcementLearner<GBMParameters,I,A extends Action<I>,Feedback<java.lang.Double>,SimpleStatelessPolicy<I,A extends Action<I>>>
getParameters
in class AbstractStatlessLearner<GBMParameters,I,A extends Action<I>,Feedback<java.lang.Double>,SimpleStatelessPolicy<I,A extends Action<I>>>
ReinforcementLearner.getParameters()
public GBMParameters makeParameters()
public void setParameters(GBMParameters params)
AbstractStatlessLearner
setParameters
in interface ReinforcementLearner<GBMParameters,I,A extends Action<I>,Feedback<java.lang.Double>,SimpleStatelessPolicy<I,A extends Action<I>>>
setParameters
in class AbstractStatlessLearner<GBMParameters,I,A extends Action<I>,Feedback<java.lang.Double>,SimpleStatelessPolicy<I,A extends Action<I>>>
edu.iastate.jrelm.rl.PA#validateParameters()
,
edu.iastate.jrelm.rl.ReinforcementLearner#setParameters(PA)
public SimpleStatelessPolicy<I,A> getPolicy()
ReinforcementLearner
getPolicy
in interface ReinforcementLearner<GBMParameters,I,A extends Action<I>,Feedback<java.lang.Double>,SimpleStatelessPolicy<I,A extends Action<I>>>
getPolicy
in class AbstractStatlessLearner<GBMParameters,I,A extends Action<I>,Feedback<java.lang.Double>,SimpleStatelessPolicy<I,A extends Action<I>>>
StatelessPolicy
public void setPolicy(SimpleStatelessPolicy<I,A> newPolicy)
ReinforcementLearner
setPolicy
in interface ReinforcementLearner<GBMParameters,I,A extends Action<I>,Feedback<java.lang.Double>,SimpleStatelessPolicy<I,A extends Action<I>>>
setPolicy
in class AbstractStatlessLearner<GBMParameters,I,A extends Action<I>,Feedback<java.lang.Double>,SimpleStatelessPolicy<I,A extends Action<I>>>
StatelessPolicy
public java.lang.String getName()
ReinforcementLearner
|
||||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |