A B C D E F G I J L M N P R S U V W

S

setBoltzmannTemp(double) - Method in class edu.iastate.jrelm.rl.rotherev.REParameters
 
setDistribution(State<SI>, double[]) - Method in class edu.iastate.jrelm.rl.SimplePolicy
Set the probability distribution function used in selecting Actions from the ActionDomain for the given State.
setDistribution(double[]) - Method in class edu.iastate.jrelm.rl.SimpleStatelessPolicy
Set the probability distribution used in selecting actions from the action domain.
setEditorEnabled(boolean) - Method in class edu.iastate.jrelm.gui.BasicSettingsEditor
Enables or disables the subpanel for editing the parameter settings.
setExperimentation(double) - Method in class edu.iastate.jrelm.rl.rotherev.REParameters
 
setFeedbackRange(double, double) - Method in class edu.iastate.jrelm.rl.bushmosteller.LinearGBMParameters
Set the range of expected reinforcement strength values.
setInitialPropensity(double) - Method in class edu.iastate.jrelm.rl.rotherev.REParameters
 
setInitialPropensityValue(double) - Method in class edu.iastate.jrelm.rl.rotherev.RELearner
Set the initial propensity value.
setLastRandSeed(int) - Method in class edu.iastate.jrelm.rl.AbstractStatlessLearner
 
setLastSelectedAction(A) - Method in class edu.iastate.jrelm.rl.AbstractStatlessLearner
 
setMultiplierValue(double) - Method in class edu.iastate.jrelm.rl.bushmosteller.LinearGBMParameters
Set the current multiplier value v used in the feedback modifier function v(r) = v * r.
setParameterList(Collection<P>) - Method in class edu.iastate.jrelm.gui.JReLMController_Mark1
 
setParameterList(Collection<P>) - Method in class edu.iastate.jrelm.gui.JReLMSettingsController_Mark2
Set the list of available reinforcement algorithms that can be set through this JReLM parameters settings window.
setParameters(PA) - Method in class edu.iastate.jrelm.rl.AbstractStatlessLearner
Note, this method will check that these parameters are valid before accepting them (PA.validate()).
setParameters(GBMParameters) - Method in class edu.iastate.jrelm.rl.bushmosteller.GBMLearner
 
setParameters(PA) - Method in interface edu.iastate.jrelm.rl.ReinforcementLearner
Sets the current settings for this learning algorithm.
setParameters(RLParameters) - Method in class edu.iastate.jrelm.rl.SimpleStatelessLearner
Set the learning parameters to use.
setPolicy(PO) - Method in class edu.iastate.jrelm.rl.AbstractStatlessLearner
 
setPolicy(SimpleStatelessPolicy<I, A>) - Method in class edu.iastate.jrelm.rl.bushmosteller.GBMLearner
 
setPolicy(PO) - Method in interface edu.iastate.jrelm.rl.ReinforcementLearner
Set the StatelessPolicy to be used to represent learned knowledge.
setPolicy(REPolicy<I, A>) - Method in class edu.iastate.jrelm.rl.rotherev.RELearner
 
setPolicy(StatelessPolicy<Integer, SimpleAction<O>>) - Method in class edu.iastate.jrelm.rl.SimpleStatelessLearner
Set the policy for this SimpleStatelessLearner.
setProbability(Object, I, double) - Method in class edu.iastate.jrelm.rl.AbstractStatelessPolicy
 
setProbability(SI, AI, double) - Method in interface edu.iastate.jrelm.rl.Policy
Updates the probability of choosing an Action from the given State.
setProbability(SI, AI, double) - Method in class edu.iastate.jrelm.rl.SimplePolicy
Set a State-Action pair probability value.
setProbability(I, double) - Method in class edu.iastate.jrelm.rl.SimpleStatelessPolicy
Updates the probability of choosing the indicated Action
setProbability(I, double) - Method in interface edu.iastate.jrelm.rl.StatelessPolicy
Updates the probability of choosing the indicated Action.
setPropensities(double[]) - Method in class edu.iastate.jrelm.rl.rotherev.REPolicy
 
setPropensity(I, double) - Method in class edu.iastate.jrelm.rl.rotherev.REPolicy
 
setPropensity(int, double) - Method in class edu.iastate.jrelm.rl.rotherev.REPolicy
 
setRandomEngine(RandomEngine) - Method in class edu.iastate.jrelm.rl.SimplePolicy
Sets the RandomEngine to be used by this policy.
setRandomEngine(RandomEngine) - Method in class edu.iastate.jrelm.rl.SimpleStatelessPolicy
Sets the RandomEngine to be used by this policy.
setRandomEngine(RandomEngine) - Method in class edu.iastate.jrelm.util.ModifiedEmpiricalWalker
 
setRandomEngine(RandomEngine) - Method in class edu.iastate.jrelm.util.SimpleEventGenerator
 
setRandomSeed(int) - Method in class edu.iastate.jrelm.rl.bushmosteller.GBMParameters
 
setRandomSeed(int) - Method in interface edu.iastate.jrelm.rl.Policy
Should reset the psuedo-random number generator used by this Policy when generating new Action selections.
setRandomSeed(int) - Method in class edu.iastate.jrelm.rl.rotherev.REParameters
Set the seed to be used with the RandomEngine used in MREPolicy
setRandomSeed(int) - Method in class edu.iastate.jrelm.rl.SimplePolicy
Resets the RandomEngine, initializing it with the given seed.
setRandomSeed(int) - Method in class edu.iastate.jrelm.rl.SimpleStatelessPolicy
Resets the RandomEngine, initializing it with the given seed.
setRecency(double) - Method in class edu.iastate.jrelm.rl.rotherev.REParameters
 
setSettingsManager(BasicLearnerManager) - Method in class edu.iastate.jrelm.gui.BasicSettingsEditor
 
setState(double[]) - Method in class edu.iastate.jrelm.util.DiscreteEventGenerator
 
setState(double[], int) - Method in class edu.iastate.jrelm.util.DiscreteEventGenerator
 
setState(double[], RandomEngine) - Method in class edu.iastate.jrelm.util.DiscreteEventGenerator
 
setState(double[], int) - Method in class edu.iastate.jrelm.util.ModifiedEmpiricalWalker
Sets the distribution parameters.
setState(double[]) - Method in class edu.iastate.jrelm.util.SimpleEventGenerator
 
setState(double[], int) - Method in class edu.iastate.jrelm.util.SimpleEventGenerator
 
setState(double[], RandomEngine) - Method in class edu.iastate.jrelm.util.SimpleEventGenerator
 
setState2(double[]) - Method in class edu.iastate.jrelm.util.ModifiedEmpiricalWalker
Modified from EmpiricalWalker to allow nextInt to work properly when the given pdf contains uniform values.
settings - Variable in class edu.iastate.jrelm.core.BasicLearnerManager
 
setup() - Method in class edu.iastate.jrelm.demo.bandit.BanditModel
 
setUpdateCount(int) - Method in class edu.iastate.jrelm.rl.AbstractStatlessLearner
 
simEventPerformed(SimEvent) - Method in class edu.iastate.jrelm.gui.BasicSettingsEditor
 
SimpleAction<O> - Class in edu.iastate.jrelm.core
Simple class that implements the Action interface.
SimpleAction(Integer, O) - Constructor for class edu.iastate.jrelm.core.SimpleAction
Make a SimpleAction, given the action representation Object and an ID.
SimpleActionDomain<O> - Class in edu.iastate.jrelm.core
SimpleActionDomain is basic implementation of the ActionDomain interface.
SimpleActionDomain(Collection<O>) - Constructor for class edu.iastate.jrelm.core.SimpleActionDomain
Build a domain from the given collection of Objects.
SimpleEventGenerator - Class in edu.iastate.jrelm.util
Generate discrete random events from a given distribution.
SimpleEventGenerator(double[]) - Constructor for class edu.iastate.jrelm.util.SimpleEventGenerator
 
SimpleEventGenerator(double[], int) - Constructor for class edu.iastate.jrelm.util.SimpleEventGenerator
 
SimpleEventGenerator(double[], RandomEngine) - Constructor for class edu.iastate.jrelm.util.SimpleEventGenerator
 
SimpleFeedback<O> - Class in edu.iastate.jrelm.core
Simple implementation of the Feedback interface.
SimpleFeedback(O) - Constructor for class edu.iastate.jrelm.core.SimpleFeedback
 
SimplePolicy<AI,A extends Action,SI,S extends State> - Class in edu.iastate.jrelm.rl
A simple implementation of the Policy interface.
SimplePolicy(ActionDomain<AI, A>, StateDomain<SI, S>) - Constructor for class edu.iastate.jrelm.rl.SimplePolicy
Construct a SimplePolicy using a given ActionDomain and StateDomain.
SimplePolicy(ActionDomain<AI, A>, StateDomain<SI, S>, int) - Constructor for class edu.iastate.jrelm.rl.SimplePolicy
Construct a SimplePolicy using a given ActionDomain, StateDomain and psuedo-random generator seed.
SimplePolicy(ActionDomain<AI, A>, StateDomain<SI, S>, RandomEngine) - Constructor for class edu.iastate.jrelm.rl.SimplePolicy
Construct a SimplePolicy using a given ActionDomain and RandomEngine.
SimplePolicy(ActionDomain<AI, A>, StateDomain<SI, S>, double[][]) - Constructor for class edu.iastate.jrelm.rl.SimplePolicy
Construct a SimplePolicy using the given ActionDomain, StateDomain, and initial probability distribution functions.
SimplePolicy(ActionDomain<AI, A>, StateDomain<SI, S>, double[][], int) - Constructor for class edu.iastate.jrelm.rl.SimplePolicy
 
SimplePolicy(ActionDomain<AI, A>, StateDomain<SI, S>, double[][], RandomEngine) - Constructor for class edu.iastate.jrelm.rl.SimplePolicy
 
SimpleState<O> - Class in edu.iastate.jrelm.core
Simple class that implements the State interface.
SimpleState(Integer, O) - Constructor for class edu.iastate.jrelm.core.SimpleState
Make a SimpleState with the given world state and an ID.
SimpleStateDomain<O> - Class in edu.iastate.jrelm.core
SimpleStateDomain is basic implementation of the StateDomain interface.
SimpleStateDomain(Collection<O>) - Constructor for class edu.iastate.jrelm.core.SimpleStateDomain
Build a domain from the given collection of Objects.
SimpleStatelessLearner<O> - Class in edu.iastate.jrelm.rl
The SimpleStatelessLearner packages together all the core learning components and a few pre-implemented reinforcement learning algorithms.
SimpleStatelessLearner(REParameters, Collection<O>) - Constructor for class edu.iastate.jrelm.rl.SimpleStatelessLearner
Build a SimpleStatelessLearner that uses a the Roth-Erev algorithm.
SimpleStatelessLearner(REParameters, SimpleActionDomain<O>) - Constructor for class edu.iastate.jrelm.rl.SimpleStatelessLearner
Build a SimpleStatelessLearner that uses the Roth-Erev algorithm with the given SimpleActionDomain.
SimpleStatelessLearner(REParameters, REPolicy<Integer, SimpleAction<O>>) - Constructor for class edu.iastate.jrelm.rl.SimpleStatelessLearner
Build a SimpleStatelessLearner that uses the Roth-Erev algorithm with the given REPolicy.
SimpleStatelessLearner(VREParameters, Collection<O>) - Constructor for class edu.iastate.jrelm.rl.SimpleStatelessLearner
Build a SimpleStatelessLearner that uses a modified version of the Roth-Erev algorithm.
SimpleStatelessLearner(VREParameters, SimpleActionDomain<O>) - Constructor for class edu.iastate.jrelm.rl.SimpleStatelessLearner
Build a SimpleStatelessLearner that uses a modified version of the Roth-Erev algorithm with the given SimpleActionDomain.
SimpleStatelessLearner(VREParameters, REPolicy<Integer, SimpleAction<O>>) - Constructor for class edu.iastate.jrelm.rl.SimpleStatelessLearner
Build a SimpleStatelessLearner that uses a modified version of the Roth-Erev algorithm with the given REPolicy.
SimpleStatelessPolicy<I,A extends Action> - Class in edu.iastate.jrelm.rl
A simple implementation of the StatelessPolicy interface.
SimpleStatelessPolicy(ActionDomain<I, A>) - Constructor for class edu.iastate.jrelm.rl.SimpleStatelessPolicy
Construct a SimpleStatelessPolicy using a given ActionDomain.
SimpleStatelessPolicy(ActionDomain<I, A>, int) - Constructor for class edu.iastate.jrelm.rl.SimpleStatelessPolicy
Construct a SimplePolicy using the given ActionDomain and psuedo-random generator seed.
SimpleStatelessPolicy(ActionDomain<I, A>, RandomEngine) - Constructor for class edu.iastate.jrelm.rl.SimpleStatelessPolicy
Construct a SimpleStatelessPolicy using a given ActionDomain and RandomEngine.
SimpleStatelessPolicy(ActionDomain<I, A>, double[]) - Constructor for class edu.iastate.jrelm.rl.SimpleStatelessPolicy
A new MersenneTwister seeded with the current time ((int)System.currentTimeMillis()) is created as the RandomEngine for this policy.
SimpleStatelessPolicy(ActionDomain<I, A>, double[], int) - Constructor for class edu.iastate.jrelm.rl.SimpleStatelessPolicy
 
SimpleStatelessPolicy(ActionDomain<I, A>, double[], RandomEngine) - Constructor for class edu.iastate.jrelm.rl.SimpleStatelessPolicy
Note: RandomGenerator does not reveal the seed value being used.
size() - Method in interface edu.iastate.jrelm.core.ActionDomain
Reports the number of Actions in this domain.
size() - Method in class edu.iastate.jrelm.core.SimpleActionDomain
 
size() - Method in class edu.iastate.jrelm.core.SimpleStateDomain
 
size() - Method in interface edu.iastate.jrelm.core.StateDomain
Reports the number of States in this domain.
size() - Method in class edu.iastate.jrelm.demo.bandit.BanditActionDomain
 
State<I> - Interface in edu.iastate.jrelm.core
For classes representing a state of the environment that an agent is operating in.
StateDomain<I,S extends State> - Interface in edu.iastate.jrelm.core
Representation of an agent's state space.
stateDomain - Variable in class edu.iastate.jrelm.rl.SimplePolicy
 
stateIDList - Variable in class edu.iastate.jrelm.rl.SimplePolicy
 
StatelessPolicy<I,A extends Action> - Interface in edu.iastate.jrelm.rl
Interface for building a stateless reinforcement learning policy.
step() - Method in class edu.iastate.jrelm.demo.bandit.BanditModel
 

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