Implementation of saturating substrate learning

Read the equation

Computes an increment proportional to remaining coherence capacity and learning drive, then stores the incremented value with an upper clip at one. Nonnegative increments require corresponding nonnegative input factors.

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 // MASTER UPDATE: φ(t+) 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

}

auto& sub = fam.substrates[fam.active_idx[sub_id]];

// MASTER UPDATE: φ(t+) = φ(t) + (1-φ(t)) × Γ × π^eff
float delta = (1.0f - sub.phi) * Gamma * pi_eff;
sub.phi = std::min(1.0f, sub.phi + delta);
sub.last_tick = t;
sub.nu *= 0.99f;  // Novelty decay
}

// MASTER UPDATE: φ(t+) = φ(t) + (1-φ(t)) × Γ × π^eff

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