framework
active
framework:connectionist-models-of-cognition-and-learningConnectionist Models of Cognition and Learning
Models where intelligence arises from organisation of connections between simple processing units, used as basis for evolutionary connectionism
Neighborhood — ranked by edge-count
Methods (1)
method
- Hebbian LearningimplementsPrinciple that correlations strengthen connections; implements distributed learning in connectionist networks without centralized supervision.
Concepts (1)
concept
- Deep LearningextendsLearning hierarchical representations of non-decomposable functions; proposed as formal equivalent to ETI process.
Frameworks (2)
framework
- Connectionist Models Of Cognitionrelated_to
- Evolutionary ConnectionismextendsProposed framework translating connectionist learning principles into natural selection domain to explain ETIs.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Central claim about the power of connectionism.
- Analogous framework for understanding how higher-level information arises from lower-level components in a collective system.
- Neural network models demonstrating how organized functional relationships emerge via unsupervised learning; basis for evolutionary connectionism analogy.
- Key property of distributed unsupervised learning.
- Necessary condition for connectionist cognition.