Uses of Interface
edu.iastate.jrelm.core.Feedback

Packages that use Feedback
edu.iastate.jrelm.core   
edu.iastate.jrelm.rl   
edu.iastate.jrelm.rl.bushmosteller   
edu.iastate.jrelm.rl.rotherev   
edu.iastate.jrelm.rl.rotherev.variant   
 

Uses of Feedback in edu.iastate.jrelm.core
 

Classes in edu.iastate.jrelm.core that implement Feedback
 class FeedbackDoubleValue
          Simple implementation of the Feedback interface for passing 'double' valued feedback to JReLM learners.
 class SimpleFeedback<O>
          Simple implementation of the Feedback interface.
 

Uses of Feedback in edu.iastate.jrelm.rl
 

Classes in edu.iastate.jrelm.rl with type parameters of type Feedback
 class AbstractStatlessLearner<PA extends RLParameters,I,A extends Action<I>,F extends Feedback,PO extends StatelessPolicy<I,A>>
          Base abstract class for ReinforcementLearner classes that implement algorithms that do not make use of external environmental states.
 interface ReinforcementLearner<PA extends RLParameters,I,A extends Action,F extends Feedback,PO extends Policy>
          For classes that implement reinforcement learning algorithms.
 

Methods in edu.iastate.jrelm.rl with parameters of type Feedback
 void SimpleStatelessLearner.update(Feedback<java.lang.Double> reward)
          Give the learner feedback resulting from its last choice of action.
 

Uses of Feedback in edu.iastate.jrelm.rl.bushmosteller
 

Methods in edu.iastate.jrelm.rl.bushmosteller with parameters of type Feedback
 void GBMLearner.update(Feedback<java.lang.Double> reward)
          Implements the core learning function according to the Generalised Bush-Mosteller model.
 

Uses of Feedback in edu.iastate.jrelm.rl.rotherev
 

Methods in edu.iastate.jrelm.rl.rotherev with parameters of type Feedback
 void RELearner.update(Feedback<java.lang.Double> feedback)
          This activates the learning process according to the modified Roth-Erev learning algorithm.
 

Uses of Feedback in edu.iastate.jrelm.rl.rotherev.variant
 

Methods in edu.iastate.jrelm.rl.rotherev.variant with parameters of type Feedback
 void VRELearner.update(Feedback<java.lang.Double> feedback, A actionToReinforce)
          Update the Policy according to the Variant Roth-Erev algorithm, but associate the given feedback with the given Action.