Perceptron

Single-layer neural network that computes weighted sum of inputs; can only represent linearly separable functions

Neighborhood — ranked by edge-count

concept

Linearly Separable Function
associated_with
A function separable by a single linear boundary; allows independent contributions of inputs to output; computable by Perceptron

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

Perceptron Modelframework0.887
Multilayer Perceptronframework0.847
Multi Layer Perceptronframework0.840
Network with hidden layers capable of representing non-linearly separable functions, enabling deep model induction
Perceptual Fieldconcept0.786
Area in space and time an agent can survey to find alternative paths to a goal; increases with collective size.
Multi-layer Perceptron (MLP)method0.783
Feed-forward neural network with hidden layers, capable of representing non-linearly separable functions.
Perceptual Learningconcept0.783
Process of inferring causes of sensory information; unified with value learning as integral aspects of free energy minimization.
Neural Networksconcept0.780
perceptual inferenceconcept0.774
The process of inferring causes of sensory inputs, a key aspect of the free-energy minimization scheme.