Read the equation
Utility first passes through softsign, making its contribution lie strictly between −0.15 and 0.15; the error term is then subtracted linearly. The combined increment can therefore be unbounded if ed_error is unbounded. The formula defines a state update, while a policy additionally requires an action space and a mapping or distribution over actions.
Terms & definitions
| Term | Meaning in this source |
|---|---|
| x | Current scalar state |
| utility | Bounded drive after softsign |
| ed_error | Linear error penalty |
How it works
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Assumptions & limits
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Original context
Read the surrounding source passage
## 3.15 Family 14: Decisive Action / Policy ``` f₁₄(x) = x + 0.15 · softsign(utility) - 0.05 · ed_error ``` **Equation Type**: Policy gradient: π(a|s) **Explanation**: Generates action outputs by amplifying utility signals and suppressing errors. The larger positive coefficient on utility makes this an action-oriented family. ## 3.16 Family 15: Global Coherence (Kehillah) ``` f₁₅(x) = x + (φ - 1) · 0.01 · (stability - x) ``` **Equation Type**: Coherence accumulator: φ-weighted convergence **Explanation**: Slowly converges toward stability using golden-ratio-weighted adjustment. Named "Kehillah" (Hebrew for "community/congregation"). This family maintains global system coherence. --- # 4. Meta-State Update Equations
Exact original notation
f₁₄(x) = x + 0.15 · softsign(utility) - 0.05 · ed_error