concept
active
concept:hebbian-plasticityHebbian Plasticity
Associative learning rule; learning of likelihood matrix A is formally identical to Hebbian plasticity.
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Claims (1)
claim
- Connection between learning rule and synaptic plasticity.
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.
- 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.
- 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
- 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.