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 inputLinks and
outputLinks contain the links on the neural layer.
| Modifier and Type | Class and Description |
|---|---|
static class |
Activation.AvgState |
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 |
static int |
BEGIN |
boolean |
blocked |
Candidate |
candidate |
Activation.StateChange |
currentStateChange |
long |
currentStateV |
static boolean |
DEBUG_OUTPUT |
SearchNode.Decision |
decision |
static int |
END |
Writable |
extension |
SearchNode.Decision |
finalDecision |
Activation.Rounds |
finalRounds |
SearchNode.Decision |
inputDecision |
Double |
inputValue |
double |
lowerBound |
long |
markedAncDesc |
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 |
Activation.Rounds |
rounds |
List<Activation.AvgState> |
searchStates |
Integer |
sequence |
Map<Integer,Position> |
slots |
Double |
targetValue |
boolean |
ubQueued |
double |
upperBound |
orInputsdoc, id, node, outputsToAndNode, outputsToOrNode, outputToInputNode, repropagateV, visited| Constructor and Description |
|---|
Activation(int id,
Document doc,
OrNode n) |
getInputActivation, linkcompareTopublic static int BEGIN
public static int END
public static final Comparator<Activation> ACTIVATION_ID_COMP
public static int MAX_SELF_REFERENCING_DEPTH
public static int MAX_PREDECESSOR_DEPTH
public static boolean DEBUG_OUTPUT
public static Activation MIN_ACTIVATION
public static Activation MAX_ACTIVATION
public Integer sequence
public double upperBound
public double lowerBound
public Activation.State avgState
public List<Activation.AvgState> searchStates
public Activation.Rounds rounds
public Activation.Rounds finalRounds
public boolean ubQueued
public long markedHasCandidate
public long currentStateV
public Activation.StateChange currentStateChange
public long markedDirty
public long markedPredecessor
public Double targetValue
public Double inputValue
public Writable extension
public SearchNode.Decision inputDecision
public SearchNode.Decision decision
public SearchNode.Decision finalDecision
public Candidate candidate
public long markedAncDesc
public boolean blocked
public Position getSlot(int slot)
public void setSlot(int slot,
Position pos)
public Integer length()
public void setTargetValue(Double targetValue)
public String getLabel()
public INeuron.Type getType()
public String getText()
public INeuron getINeuron()
public Neuron getNeuron()
public void addLink(Linker.Direction dir, Activation.Link l)
public Activation.Link getLinkBySynapseId(int synapseId)
public SortedSet<Activation.Link> getInputLinksOrderedBySynapse()
public Stream<Activation.Link> getInputLinks(boolean includePassive, boolean onlySelected)
public Stream<Activation.Link> getOutputLinks(boolean includePassive)
public Activation.Link getInputLink(Activation.Link l)
public Stream<Activation.Link> getInputLinksBySynapse(boolean includePassive, Synapse syn)
public Stream<Activation.Link> getOutputLinksBySynapse(boolean includePassive, Synapse syn)
public double process(SearchNode sn, int round, long v)
public Activation.State computeValueAndWeight(int round)
public boolean isActiveable()
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 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 withLogic)
public String slotsToString()
public String identityToString()
public String linksToString()
public void saveOldState(Map<Activation,Activation.StateChange> changes, long v)
public void saveNewState()
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