concept
active
concept:concept-learningConcept Learning
Acquisition of new concepts by Bayesian model expansion and reduction.
Neighborhood — ranked by edge-count
Concepts (1)
concept
- Learningrelated_toInference of parameters encoding contingencies of the world (e.g., likelihood matrix A) at slower timescale than perception.
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 entity of Jackson's framework: a structure invented to give coherent account of immediate consequences of actions; the building block of software design
- Updating the structure of the generative model to better account for observations via Bayesian model reduction and expansion.
- 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
- Field of research integrating reward learning and optimization; shown to be unified with perceptual learning via free energy principle.
- How a neural network encodes a semantic concept internally, argued to be better captured by manifolds than by atomic features.
- Probabilistic framework formalizing concept-specific subspaces for targeted steering in generative models.