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Packages that use Feedback | |
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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 |
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Classes in edu.iastate.jrelm.core that implement Feedback | |
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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 |
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Classes in edu.iastate.jrelm.rl with type parameters of type Feedback | |
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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 | |
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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 |
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Methods in edu.iastate.jrelm.rl.bushmosteller with parameters of type Feedback | |
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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 |
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Methods in edu.iastate.jrelm.rl.rotherev with parameters of type Feedback | |
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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 |
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Methods in edu.iastate.jrelm.rl.rotherev.variant with parameters of type Feedback | |
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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. |
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