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Packages that use Dimension | |
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clarion.system | |
clarion.tools |
Uses of Dimension in clarion.system |
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Methods in clarion.system that return Dimension | |
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Dimension |
Dimension.clone()
Clones the dimension (including all of it's Values). |
Dimension |
Goal.put(java.lang.Object key,
Dimension dim)
Puts the dimension into the goal as long as the dimension is not already in the goal. |
Dimension |
DimensionValueCollection.put(java.lang.Object key,
Dimension dim)
Puts the dimension into the dimension-value collection as long as the dimension is not already in the dimension-value collection. |
Dimension |
AbstractAction.put(java.lang.Object key,
Dimension dim)
Puts the dimension into the action as long as the dimension is not already in the action. |
Methods in clarion.system that return types with arguments of type Dimension | |
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java.util.Collection<Dimension> |
AbstractImplicitModule.getInput()
Gets the input nodes in the form of a dimension-value collection. |
java.util.Collection<Dimension> |
CLARION.getInternalInputSpace()
Gets the internal representation of the input space from this instance of CLARION. |
java.util.Collection<Dimension> |
QBPNet.getNewInput()
Returns the new input in the form of a dimension-value collection. |
java.util.Collection<Dimension> |
InterfaceHandlesNewInput.getNewInput()
Gets the new inputs. |
Methods in clarion.system with parameters of type Dimension | |
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Dimension |
Goal.put(java.lang.Object key,
Dimension dim)
Puts the dimension into the goal as long as the dimension is not already in the goal. |
Dimension |
DimensionValueCollection.put(java.lang.Object key,
Dimension dim)
Puts the dimension into the dimension-value collection as long as the dimension is not already in the dimension-value collection. |
Dimension |
AbstractAction.put(java.lang.Object key,
Dimension dim)
Puts the dimension into the action as long as the dimension is not already in the action. |
Method parameters in clarion.system with type arguments of type Dimension | |
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double |
GeneralizedConditionChunk.getStrength(java.util.Collection<? extends Dimension> CurrentInput)
Gets the strength of the condition based on the current input. |
void |
Goal.putAll(java.util.Map<? extends java.lang.Object,? extends Dimension> map)
Puts all of the dimensions in the map into the goal as long as the dimensions are not already in the goal. |
void |
DimensionValueCollection.putAll(java.util.Map<? extends java.lang.Object,? extends Dimension> map)
Puts all of the dimensions in the map into the dimension-value collection as long as the dimensions are not already in the dimension-value collection. |
void |
AbstractAction.putAll(java.util.Map<? extends java.lang.Object,? extends Dimension> map)
Puts all of the dimensions in the specified map into the action as long as the dimensions are not already in the action. |
void |
QBPNet.setNewInput(java.util.Collection<Dimension> input)
Sets the activations for the new input to the specified input. |
void |
InterfaceHandlesNewInput.setNewInput(java.util.Collection<Dimension> input)
Sets the new input. |
protected void |
CLARION.updateInputSpace(java.util.Collection<Dimension> c)
Updates the input space based on the specified collection of dimension-value pairs. |
protected void |
AbstractSubsystem.updateInputSpace(java.util.Collection<Dimension> c)
Updates the input space based on the specified collection of dimension-value pairs. |
protected void |
AbstractIntermediateModule.updateInputSpace(java.util.Collection<Dimension> c)
Updates the input space based on the specified collection of dimension-value pairs. |
Constructor parameters in clarion.system with type arguments of type Dimension | |
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AbstractAction(java.lang.Object id,
java.util.Collection<? extends Dimension> dims)
Initializes the action with the specified ID and dimensions. |
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AbstractAction(java.lang.Object id,
java.util.Map<? extends java.lang.Object,? extends Dimension> dims)
Initializes the action with the specified ID and map of dimensions. |
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AbstractChunk(java.lang.Object id,
java.util.Collection<? extends Dimension> dims)
Initializes the chunk with the specified ID and dimensions. |
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AbstractChunk(java.lang.Object id,
java.util.Map<? extends java.lang.Object,? extends Dimension> dims)
Initializes the chunk with the specified ID and map of dimensions. |
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AbstractEquation(java.util.Collection<Dimension> InputSpace,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs)
Initializes an equation. |
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AbstractImplicitModule(java.util.Collection<Dimension> InputSpace,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs)
Initializes an implicit module. |
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AbstractNeuralNet(java.util.Collection<Dimension> InputSpace,
int NumHidden,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs)
Initializes a neural network. |
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AbstractOutputChunk(java.lang.Object id,
java.util.Collection<? extends Dimension> dims)
Initializes the output chunk with the specified ID and dimensions. |
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AbstractOutputChunk(java.lang.Object id,
java.util.Map<? extends java.lang.Object,? extends Dimension> dims)
Initializes the output chunk with the specified ID and map of dimensions. |
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AbstractRuntimeTrainableBPNet(java.util.Collection<Dimension> InputSpace,
int NumHidden,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs)
Initializes a backpropagating neural network that is capable of being trained during runtime. |
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AbstractRuntimeTrainableImplicitModule(java.util.Collection<Dimension> InputSpace,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs)
Initializes an implicit module that is capable of being trained during runtime. |
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AbstractTrainableImplicitModule(java.util.Collection<Dimension> InputSpace,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs)
Initializes the trainable implicit module. |
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ACSLevelProbabilitySettingEquation(java.util.Collection<Dimension> InputSpace,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs)
Initializes the ACS level probability setting equation. |
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BPNet(java.util.Collection<Dimension> InputSpace,
int NumHidden,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs)
Initializes a backpropagating neural network. |
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DimensionValueCollection(java.util.Collection<? extends Dimension> dims)
Initializes a dimension-value collection with the collection of dimensions specified. |
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DimensionValueCollection(java.util.Map<? extends java.lang.Object,? extends Dimension> map)
Initializes the dimension-value collection with the map of dimensions. |
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DriveEquation(java.lang.Object id,
java.util.Collection<Dimension> InputSpace,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs)
Initializes a drive equation. |
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ExternalAction(java.lang.Object id,
java.util.Collection<? extends Dimension> dims)
Initializes the external action with the specified ID and dimensions. |
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ExternalAction(java.lang.Object id,
java.util.Map<? extends java.lang.Object,? extends Dimension> dims)
Initializes the external action with the specified ID and map of dimensions. |
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GeneralizedConditionChunk(java.util.Collection<? extends Dimension> dims)
Initializes a condition with the collection of dimensions specified. |
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GeneralizedConditionChunk(java.util.Map<? extends java.lang.Object,? extends Dimension> map)
Initializes the condition with the map of dimensions. |
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Goal(java.lang.Object id,
java.util.Collection<? extends Dimension> dims)
Initializes the goal with the specified ID and dimensions. |
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Goal(java.lang.Object id,
java.util.Map<? extends java.lang.Object,? extends Dimension> dims)
Initializes the goal with the specified ID and map of dimensions. |
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GoalAction(java.lang.Object id,
java.util.Collection<? extends Dimension> dims)
Initializes the goal action with the specified ID and dimensions. |
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GoalAction(java.lang.Object id,
java.util.Map<? extends java.lang.Object,? extends Dimension> dims)
Initializes the goal action with the specified ID and map of dimensions. |
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GoalSelectionEquation(java.util.Collection<Dimension> InputSpace,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs)
Initializes the goal selection equation. |
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QBPNet(java.util.Collection<Dimension> InputSpace,
int NumHidden,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs)
Initializes a backpropagating neural network that uses Q-Learning for training the network. |
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SimplifiedQBPNet(java.util.Collection<Dimension> InputSpace,
int NumHidden,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs)
Initializes a backpropagating neural network that uses simplified Q-Learning for training the network. |
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TableLookup(java.util.Collection<Dimension> InputSpace,
AbstractOutputChunkCollection<? extends AbstractOutputChunk> Outputs,
java.util.Map<DimensionValueCollection,AbstractOutputChunkCollection<? extends AbstractOutputChunk>> Table)
Initializes the table lookup with the input space, outputs, and map specified. |
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WorkingMemoryAction(java.lang.Object id,
java.util.Collection<? extends Dimension> dims)
Initializes the working memory action with the specified ID and dimensions. |
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WorkingMemoryAction(java.lang.Object id,
java.util.Map<? extends java.lang.Object,? extends Dimension> dims)
Initializes the working memory action with the specified ID and map of dimensions. |
Uses of Dimension in clarion.tools |
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Methods in clarion.tools with parameters of type Dimension | |
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private void |
TrainableImplicitModulePreTrainer.innerLoop(AbstractTrainableImplicitModule target,
AbstractImplicitModule trainer,
java.util.ListIterator<Dimension> dim,
java.util.ListIterator<? extends Value> val,
Dimension d,
Value v,
TrainableImplicitModulePreTrainer.SumSquaredErrorTracker sqe)
The inner loop of the dataRecursor method. |
Method parameters in clarion.tools with type arguments of type Dimension | |
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private void |
TrainableImplicitModulePreTrainer.dataRecursor(AbstractTrainableImplicitModule target,
AbstractImplicitModule trainer,
java.util.ListIterator<Dimension> dim,
java.util.ListIterator<? extends Value> val,
TrainableImplicitModulePreTrainer.SumSquaredErrorTracker sqe)
Recursive method that iterates over the dimensions of a dimension-value collection (from the data set and trains the specified target implicit module based on the outputs from the specified trainer implicit module. |
private void |
TrainableImplicitModulePreTrainer.innerLoop(AbstractTrainableImplicitModule target,
AbstractImplicitModule trainer,
java.util.ListIterator<Dimension> dim,
java.util.ListIterator<? extends Value> val,
Dimension d,
Value v,
TrainableImplicitModulePreTrainer.SumSquaredErrorTracker sqe)
The inner loop of the dataRecursor method. |
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