Learning-drive product

Read the equation

Scales learning by the product of activation, plasticity and confidence. The product couples readiness to learn with rate and evidence strength.

Terms & definitions

The recovered passage does not supply a separate symbol table. Read the source context for the notation used in this version; familiar letters may carry different meanings in other builds.

How it works

1. Read 4. Learning drive: Γ as the quantity being defined or updated by this relation.

2. Substitute the source-defined variables or recorded values and follow the displayed arithmetic and indexing exactly.

3. Use this version’s variable definitions and update order. The same symbol may be assigned a different meaning in another build.

Assumptions & limits

Source recovery establishes that the expression appears in this record. Its mathematical validity, implementation behavior, and interpretation must be assessed separately. See the linked source and research notes for the checks available for this version.

Original context

2. Compute activation:    χ = 1 / (1 + e^(-(α_κ·κ + α_Ψ·Ψ̃ - θ)))

3. Bound plasticity:      η = clamp(η_base + η_gain·κ, η_min, η_max)

4. Learning drive:        Γ = χ × η × κ

PARAMETERS (config/tuned_weights_v2.env)

SEFERIM_ALPHA_KAPPA = 3.0      # Weight of local confidence κ
SEFERIM_ALPHA_PSI   = 2.0      # Weight of normalized pressure Ψ̃

4. Learning drive:        Γ = χ × η × κ

Related builds