concept
active
concept:hebbian-plasticity

Hebbian Plasticity

Associative learning rule; learning of likelihood matrix A is formally identical to Hebbian plasticity.

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Related by similarity (8)

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.

  • Synaptic update rule that is formally identical to associative learning; used for learning A.
  • The Self is not fixed; its boundaries, goals, and substrate can change during the lifetime of an agent.
  • Hebbian Learningmethod0.749
    Principle that correlations strengthen connections; implements distributed learning in connectionist networks without centralized supervision.
  • The ability of biological structures to adjust to perturbations (injury, internal modifications) and still accomplish adaptive tasks across multiple problem spaces.
  • Experience-dependent changes in synaptic weights, implementing learning of A, B, D matrices.
  • Plasticity in reproduction timing or mode cued by collective context, equalizing fitnesses in egalitarian transitions
  • Plasticityconcept0.731
    Property of minds to adapt to radical changes in substrate, form, and embodiment across lifetime and evolution.
  • Learning mechanism: parameter updates resemble classical Hebbian learning with associative and decay terms.