net.sourceforge.jabm.learning
Class MetaLearner

java.lang.Object
  net.sourceforge.jabm.learning.AbstractLearner
      net.sourceforge.jabm.learning.MetaLearner

All Implemented Interfaces:

java.io.Serializable, DiscreteLearner, Learner, StimuliResponseLearner

public class MetaLearner
extends AbstractLearner
implements StimuliResponseLearner, java.io.Serializable

See Also:

Serialized Form

Field Summary

protected int	currentLearner
protected StimuliResponseLearner	masterLearner
protected StimuliResponseLearner[]	subLearners

Fields inherited from class net.sourceforge.jabm.learning.AbstractLearner

monitor

Constructor Summary

MetaLearner()

MetaLearner(int numLearners)

Method Summary

int	act() Request that the learner perform an action.
int	bestAction()
void	dumpState(DataWriter out) Write out our state data to the specified data writer.
double	getLearningDelta() Return a value indicative of the amount of learning that occured during the last iteration.
int	getNumberOfActions() Get the number of different possible actions this learner can choose from when it performs an action.
void	reward(double reward) Reward the learning algorithm according to the last action it chose.
int	worstAction()

Methods inherited from class net.sourceforge.jabm.learning.AbstractLearner

monitor

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface net.sourceforge.jabm.learning.Learner

monitor

Field Detail

currentLearner

protected int currentLearner

subLearners

protected StimuliResponseLearner[] subLearners

masterLearner

protected StimuliResponseLearner masterLearner

Constructor Detail

MetaLearner

public MetaLearner()

MetaLearner

public MetaLearner(int numLearners)

Method Detail

act

public int act()

Description copied from interface: DiscreteLearner

Request that the learner perform an action. Users of the learning algorithm should invoke this method on the learner when they wish to find out which action the learner is currently recommending.

Specified by:

act in interface DiscreteLearner

Returns:

An integer representing the action to be taken.

reward

public void reward(double reward)

Description copied from interface: StimuliResponseLearner

Reward the learning algorithm according to the last action it chose.

Specified by:

reward in interface StimuliResponseLearner

getLearningDelta

public double getLearningDelta()

Description copied from interface: Learner

Return a value indicative of the amount of learning that occured during the last iteration. Values close to 0.0 indicate that the learner has converged to an equilibrium state.

Specified by:

getLearningDelta in interface Learner

Specified by:

getLearningDelta in class AbstractLearner

Returns:

A double representing the amount of learning that occured.

getNumberOfActions

public int getNumberOfActions()

Description copied from interface: DiscreteLearner

Get the number of different possible actions this learner can choose from when it performs an action.

Specified by:

getNumberOfActions in interface DiscreteLearner

Returns:

An integer value representing the number of actions available.

dumpState

public void dumpState(DataWriter out)

Description copied from interface: Learner

Write out our state data to the specified data writer.

Specified by:

dumpState in interface Learner

Specified by:

dumpState in class AbstractLearner

bestAction

public int bestAction()

Specified by:

bestAction in interface StimuliResponseLearner

worstAction

public int worstAction()

Specified by:

worstAction in interface StimuliResponseLearner