method
active
method:local-learning-rule

Local learning rule

Learning rule where change in a parameter at point x,t depends only on system state at same or nearby spacetime points, without requiring global cost function computation

Neighborhood — ranked by edge-count

Frameworks (1)

framework
  • Framework for solving inverse problems in which physical systems autonomously adapt their parameters in response to stimuli through local learning rules, without requiring computational design or explicit cost functions

Methods (1)

method
  • Biologically plausible local learning rule constraining the brain; referenced as precedent for locality-constrained learning in physical systems

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.

  • Learningconcept0.768
    Inference of parameters encoding contingencies of the world (e.g., likelihood matrix A) at slower timescale than perception.
  • Habit Learningconcept0.748
    Learning through Bayesian model averaging over policies, leading to habitual behavior.
  • Experimental simulation paradigm where agents learn a rule mapping central cue color to correct response location
  • Process of inferring causes of sensory information; unified with value learning as integral aspects of free energy minimization.
  • The principle that decision-making about centers must be decentralized to the people closest to them to achieve a living environment.
  • Q-learningmethod0.719
    Model-free RL algorithm used in experimental comparison; employs ε-greedy exploration.
  • Bottom-up learningconcept0.716
    Distributed learning that arises from local component interactions without system-level supervision or global feedback.
  • Early learningconcept0.716
    The primary domain in which Nicholson's Theory of Loose Parts became influential and known.