CIRCUIT COMPONENTS

associator

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Hetero-associative memory component for supervised learning.

See also: https://creatingintelligence.org/#supervised-learning

Details and properties

  • Wrapper for a hetero-associative topological memory instance.
  • Receives the label from its first receive block and data from the remaining blocks.
  • Training is triggered if the label input is non-empty.
  • Inference is triggered by an empty label input.
  • Sends the inferred label.
  • Resolves multiset and inibitory input prior to processing.


Property Default Description
send required integer, representing a single output slot
receive required two or more input slots with pathway tags
threshold automatic relative pattern matching threshold
decimate 1 proportional stochastic decimation applied to training data


Use standard style options to customize the component’s appearance in circuit schematics.

Supervised learning

A basic supervised learning setup using hetero-associative memory:

{ "hyperparameters": {"default": [1000, 10]},
  "dataflow": [
    {"component": "input", "send": [1], "label": "label"},
    {"component": "input", "send": [2], "label": "data"},
    {"component": "associator", "send": [11], "receive": [1, 2]},
    {"component": "output", "receive": [11]}
  ]}

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