public final class Activation extends OrNode.OrActivation
Activation class is the most central class in Aika. On the one hand it stores the activation value
for a given neuron in the State substructure. On the other hand it specifies where this activation is
located within the document and to which interpretation it belongs. The Activation.Key therefore
consists of the logic node to which this activation belongs. If this logic node is an or-node, then this activation
automatically also belongs to the neuron as well. Furthermore, the key contains the char range within the document
and the relational id (rid). The relational id might be used to store the word pos for instance. Lastly, the key
contain the interpretation node of this activation, specifying to which interpretation this activation belongs.
The activations are linked to each other on two levels. The fields inputs and outputs
contain the activation links within the logic layer. The fields neuronInputs and
neuronOutputs contain the links on the neural layer.
| Modifier and Type | Class and Description |
|---|---|
static class |
Activation.Builder |
static class |
Activation.Link
The
SynapseActivation mirror the synapse link in the network of activations. |
static class |
Activation.Mode |
static class |
Activation.Rounds
Since Aika is a recurrent neural network, it is necessary to compute several rounds of activation values.
|
static class |
Activation.State
A
State object contains the activation value of an activation object that belongs to a neuron. |
class |
Activation.StateChange
The
StateChange class is used to store the state change of an activation that occurs in each node of
the binary search tree. |
| Modifier and Type | Field and Description |
|---|---|
static Comparator<Activation> |
ACTIVATION_ID_COMP |
Activation.State |
avgState |
Candidate |
candidate |
Activation.StateChange |
currentStateChange |
long |
currentStateV |
SearchNode.Decision |
decision |
double |
errorSignal |
SearchNode.Decision |
finalDecision |
Activation.Rounds |
finalRounds |
SearchNode.Decision |
inputDecision |
Double |
inputValue |
boolean |
isQueued |
double |
lowerBound |
long |
markedAncestor |
long |
markedDirty |
long |
markedHasCandidate |
long |
markedPredecessor |
static Activation |
MAX_ACTIVATION |
static int |
MAX_PREDECESSOR_DEPTH |
static int |
MAX_SELF_REFERENCING_DEPTH |
static Activation |
MIN_ACTIVATION |
TreeMap<Activation.Link,Activation.Link> |
neuronInputs |
TreeMap<Activation.Link,Activation.Link> |
neuronOutputs |
long |
queueId |
Range |
range |
Activation.Rounds |
rounds |
Map<Integer,Activation.State> |
searchStates |
TreeSet<Activation.Link> |
selectedNeuronInputs |
Integer |
sequence |
Double |
targetValue |
boolean |
ubQueued |
double |
upperBound |
inputsdoc, id, node, outputsToAndNode, outputsToOrNode, outputToInputNode, repropagateV, visited| Constructor and Description |
|---|
Activation(int id,
Document doc,
OrNode n) |
Activation(int id,
Document doc,
Range r,
OrNode n) |
getInputActivation, linkcompareTopublic static final Comparator<Activation> ACTIVATION_ID_COMP
public static int MAX_SELF_REFERENCING_DEPTH
public static int MAX_PREDECESSOR_DEPTH
public static Activation MIN_ACTIVATION
public static Activation MAX_ACTIVATION
public Range range
public TreeSet<Activation.Link> selectedNeuronInputs
public TreeMap<Activation.Link,Activation.Link> neuronInputs
public TreeMap<Activation.Link,Activation.Link> neuronOutputs
public Integer sequence
public double upperBound
public double lowerBound
public Activation.State avgState
public Map<Integer,Activation.State> searchStates
public Activation.Rounds rounds
public Activation.Rounds finalRounds
public boolean ubQueued
public boolean isQueued
public long queueId
public long markedHasCandidate
public long currentStateV
public Activation.StateChange currentStateChange
public long markedDirty
public long markedPredecessor
public double errorSignal
public Double targetValue
public Double inputValue
public SearchNode.Decision inputDecision
public SearchNode.Decision decision
public SearchNode.Decision finalDecision
public Candidate candidate
public long markedAncestor
public void setTargetValue(Double targetValue)
public String getLabel()
public String getText()
public INeuron getINeuron()
public Neuron getNeuron()
public void addSynapseActivation(Linker.Direction dir, Activation.Link sa)
public double process(SearchNode sn, int round, long v)
public Activation.State computeValueAndWeight(int round)
public void processBounds()
public void computeBounds()
public List<Activation.Link> getFinalInputActivationLinks()
public List<Activation.Link> getFinalOutputActivationLinks()
public Collection<Activation> getConflicts()
public void adjustSelectedNeuronInputs(SearchNode.Decision d)
public Activation getTarget()
public boolean checkSelfReferencing(boolean onlySelected,
int depth,
long v)
public void setDecision(SearchNode.Decision newDecision, long v)
public boolean isFinalActivation()
public Activation.State getFinalState()
public Integer getSequence()
public void markDirty(long v)
public void markPredecessor(long v,
int depth)
public String toString(boolean finalOnly, boolean withTextSnippet, boolean withLogic)
public String linksToString()
public void saveOldState(Map<Activation,Activation.StateChange> changes, long v)
public void saveNewState()
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