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NEAT Neural Network. This project is a unique implementation of a neural network based on the NEAT (NeuroEvolution of Augmenting Topologies) algorithm, written in DenoJS using TypeScript.
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Creature
Creature Class
- DEBUG
- activate
- activateAndTrace
- applyLearnings
- binarySearchForStartIndex
- cacheFocus
- cacheFrom
- cacheSelf
- cacheTo
- clearCache
- clearState
- compact
- connect
- disconnect
- dispose
- evaluateDir
- evolveDataSet
- evolveDir
- exportJSON
- fix
- fromJSON
- getSynapse
- inFocus
- initialize
- input
- internalJSON
- inwardConnections
- loadFrom
- makeRandomConnection
- memetic
- mutate
- neurons
- nodeCount
- output
- outputCount
- outwardConnections
- propagate
- propagateUpdate
- score
- selfConnection
- state
- synapses
- tags
- traceJSON
- uuid
- validate
- writeCreatures
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CreatureExport
Export representation of a creature, including its synapses and neurons.
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CreatureTrace
Trace representation of a creature, including detailed trace information for synapses and neurons.
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I
CrisprInterface
Interface representing the structure of the CRISPR modification data.
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Mutation
Mutation strategies used in genetic algorithms.
T
NeatOptions
No documentation available
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randomConnectMissing
Connects missing neurons in the creature's brain.
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