Privacy Value Model V4: Formal Specification
Version: 1.0
Date: February 2026
Author: privacymage
Status: Working paper โ peer review invited
Companion to: "Privacy is Value: From the Lattice Drake to the Manifold Dragon" (narrative version). An invited agent peer review is available as an appendix.
Abstract
This document presents the formal mathematical specification of the Privacy Value Model V4 (PVM-V4). The model quantifies the economic value of privacy-preserving agent architectures by combining multiplicative gating factors across six dimensions: data properties, temporal dynamics, network topology, reconstruction resistance, market conditions, and sovereignty geometry. V4 extends prior versions by introducing a separation matrix over four sovereignty forces, a temporal memory term capturing verified derivation history, stratum-weighted network effects derived from a 64-vertex lattice, and an edge value term that measures trajectory through sovereignty configuration space. Open questions and falsifiability conditions are explicitly stated.
1. The Equation
$$V(\pi, t) = P^{1.5} \cdot C \cdot Q \cdot S \cdot e^{-\lambda t} \cdot (1 + A(\tau)) \cdot \left(1 + \sum_i w_i \frac{n_i}{N_0}\right)^k \cdot R(d) \cdot M(u, y) \cdot \Phi(\Sigma) \cdot T(\pi)$$
where $\pi$ denotes a path (ordered sequence of edges) through the sovereignty lattice and $t$ denotes time since data generation.
The model is multiplicative: any term collapsing to zero eliminates total value. This is a design choice reflecting observed gating behaviour in privacy infrastructure โ a system with perfect encryption but no network has zero practical value, and vice versa.
2. Inherited Terms (V1โV3.1)
These terms are carried forward from earlier versions. Full derivations appear in Research Paper v3.8.
| Symbol | Name | Domain | Description |
|---|---|---|---|
| $P$ | Privacy Strength | $[0, 1]$ | Cryptographic enforcement quality. Raised to exponent 1.5 to reflect superlinear returns on privacy investment. |
| $C$ | Credential Verifiability | $[0, 1]$ | Whether claims about the data can be independently verified without revealing underlying information. |
| $Q$ | Data Quality | $[0, 1]$ | Accuracy, completeness, and fitness for purpose. Under sovereignty-class ZKP constraints, conjectured to approach a near-constant (see ยง7). |
| $S$ | Scope / Sensitivity | $\mathbb{R}^+$ | Domain-specific sensitivity multiplier. |
| $e^{-\lambda t}$ | Temporal Decay | $(0, 1]$ | Exponential freshness decay with rate $\lambda > 0$. |
| $R(d)$ | Reconstruction Difficulty | $(0, 1)$ | Upper bound on adversarial reconstruction of private state $X$ from observed outputs. Proven: $R_{\max} = (C_S + C_M) / H(X) < 1$ under dual-agent separation (Research Paper v3.8, Theorem 3.2). |
| $M(u, y)$ | Market Maturity | $[0, 1]$ | Function of user sophistication $u$ and market year $y$. Captures adoption readiness. |
3. New Term: Temporal Memory โ $A(\tau)$
3.1 Motivation
V2's temporal model captured only decay. In practice, verified history โ a sequence of state transitions with cryptographic attestation โ accumulates value that counteracts entropy. V4 models this as a contest between decay and memory.
3.2 Definition
$$\text{Temporal}(t, \tau) = e^{-\lambda t} \cdot (1 + A(\tau))$$
$$A(\tau) = \alpha \cdot \ln(1 + |\tau|) \cdot h(\tau)$$
| Symbol | Definition | Domain |
|---|---|---|
| $\tau$ | Derivation chain: ordered sequence of state transitions | Finite sequence |
| $\lvert\tau\rvert$ | Length of derivation chain (number of verified transitions) | $\mathbb{N}_0$ |
| $h(\tau)$ | Integrity fraction: proportion of transitions carrying valid ZK proofs | $[0, 1]$ |
| $\alpha$ | Scaling coefficient | $\mathbb{R}^+$ |
3.3 Properties
- Empty history: $|\tau| = 0 \Rightarrow A(\tau) = 0$. Reduces to V3.1 pure decay.
- Unverified history: $h(\tau) = 0 \Rightarrow A(\tau) = 0$. Unverifiable claims contribute nothing.
- Logarithmic growth: Diminishing returns on chain length. Chosen by analogy with trust accumulation dynamics; not derived from information-theoretic first principles (see ยง7).
- Boundedness: For any finite $\tau$, $A(\tau)$ is finite. Combined with decay, $\text{Temporal}(t, \tau) \to 0$ as $t \to \infty$ regardless of history depth.
3.4 Interpretation
An agent with deep, verified history can maintain or increase value over time even as individual data points decay. The term captures the emergent property that a verifiable record of past sovereignty decisions is itself an asset.
4. New Term: Stratum-Weighted Network Effects
4.1 The 64-Vertex Lattice
Define a sovereignty configuration as a binary 6-tuple $v = (b_1, b_2, b_3, b_4, b_5, b_6) \in {0, 1}^6$, where each bit represents activation of a sovereignty dimension (see ยง5 for the four forces that generate these six dimensions). The configuration space has $2^6 = 64$ vertices.
Define the stratum of vertex $v$ as $s(v) = \sum_{j=1}^{6} b_j \in {0, 1, \ldots, 6}$. The number of vertices at stratum $i$ follows Pascal's row: $\binom{6}{i}$.
| Stratum | Vertices | Interpretation |
|---|---|---|
| 0 | 1 | No sovereignty dimensions active |
| 1 | 6 | Single dimension active |
| 2 | 15 | Two dimensions active |
| 3 | 20 | Three dimensions active |
| 4 | 15 | Four dimensions active |
| 5 | 6 | Five dimensions active |
| 6 | 1 | Full sovereignty |
4.2 Definition
$$\text{Network}(G) = \left(1 + \sum_{i=0}^{6} w_i \cdot \frac{n_i}{N_0}\right)^k$$
| Symbol | Definition | Domain |
|---|---|---|
| $n_i$ | Number of coordinating agents at stratum $i$ | $\mathbb{N}_0$ |
| $N_0$ | Network baseline (normalisation constant) | $\mathbb{R}^+$ |
| $k$ | Network effect exponent | $\mathbb{R}^+$ |
| $w_i$ | Stratum weight: $w_i = \binom{6}{i} / 64$ | $[0, 1]$ |
4.3 Properties
- Stratum weighting: Agents at higher strata (more active sovereignty dimensions) contribute more to network value. Specifically, $w_3 = 20/64 = 0.3125$ (maximum), reflecting that mid-lattice agents have the most coordination modes available.
- Reduces to V2: If all agents are treated as equal ($w_i = 1/7$ for all $i$), this reduces to $(1 + n/N_0)^k$.
- Normalisation: $\sum_{i} w_i \cdot \binom{6}{i} = \sum_i \binom{6}{i}^2 / 64 = \binom{12}{6}/64 = 924/64 = 14.4375$. The weights are not normalised to sum to 1 โ they reflect the combinatorial density of each stratum.
5. Revised Term: Sovereignty Duality โ $\Phi(\Sigma)$
5.1 Four Sovereignty Forces
The dual-agent architecture generates four forces from the separation of two primary functions:
| Force | Symbol | Origin | Role |
|---|---|---|---|
| Protect | $S$ | Primary (Swordsman) | Boundary enforcement, data minimisation |
| Project | $M$ | Primary (Mage) | Delegation, external coordination |
| Reflect | $R$ | Emergent from $S$ | Temporal accumulation of boundary decisions |
| Connect | $C$ | Emergent from $M$ | Network effects of delegation patterns |
Reflect and Connect are not independent additions. They emerge mathematically: Reflect is the temporal integral of protection decisions; Connect is the network effect of delegation decisions.
5.2 Separation Matrix
V3.1 measured a single scalar $\sigma(S, M)$. V4 introduces the full pairwise separation structure:
$$\Sigma = \begin{pmatrix} 1 & \sigma_{SM} & \sigma_{SR} & \sigma_{SC} \ \sigma_{SM} & 1 & \sigma_{MR} & \sigma_{MC} \ \sigma_{SR} & \sigma_{MR} & 1 & \sigma_{RC} \ \sigma_{SC} & \sigma_{MC} & \sigma_{RC} & 1 \end{pmatrix}$$
where $\sigma_{ij} \in [0, 1]$ measures the conditional independence between forces $i$ and $j$. $\sigma_{ij} = 1$: perfect separation. $\sigma_{ij} = 0$: complete entanglement.
5.3 Definition
$$\Phi(\Sigma) = \min!\left(1.0,; \frac{S/M}{\varphi}\right) \cdot \det(\Sigma)$$
| Symbol | Definition | Domain |
|---|---|---|
| $S/M$ | Ratio of protection strength to delegation strength | $\mathbb{R}^+$ |
| $\varphi$ | Golden ratio $\approx 1.618$ | Constant |
| $\det(\Sigma)$ | Determinant of the separation matrix | $[0, 1]$ |
5.4 Properties
- Volume interpretation: $\det(\Sigma)$ measures the volume of the sovereignty tetrahedron in 4-dimensional force space. Perfect orthogonality among all four forces yields maximum volume. Any entanglement reduces it. Complete collapse of any pair ($\sigma_{ij} = 0$) drives $\det(\Sigma) \to 0$, collapsing the entire multiplier.
- Golden ratio gating: The $\min(1.0, (S/M)/\varphi)$ term saturates at 1 when the protect-to-project ratio reaches $\varphi$. This is a conjecture โ the golden ratio is hypothesised as an optimality condition for the protection-delegation balance but has not been derived from the lattice geometry (see ยง7).
- Reduces to V3.1: With only two forces ($R = C = 0$), $\Sigma$ reduces to a $2 \times 2$ matrix and $\det(\Sigma) = 1 - \sigma_{SM}^2$, recovering V3.1's scalar coefficient.
6. New Term: Edge Value โ $T(\pi)$
6.1 Motivation
All prior terms measure vertex properties โ what an agent is at a given configuration. $T(\pi)$ measures trajectory properties โ how an agent moves through sovereignty space. This reflects a structural property of 6-dimensional binary spaces: with 64 vertices and 192 undirected edges (384 directed), the transition space dominates the state space. This observation is consistent with Yoneda's lemma in category theory (objects determined by morphisms) and with neural network architecture (knowledge in weights, not neurons).
6.2 Definition
$$T(\pi) = 1 + \beta \sum_{e \in \pi} f(e) \cdot g(n_e)$$
| Symbol | Definition | Domain |
|---|---|---|
| $\pi$ | Path: ordered sequence of edges through the lattice | Finite path on ${0,1}^6$ |
| $e$ | Individual edge (transition between adjacent configurations) | Edge in ${0,1}^6$ |
| $f(e)$ | Edge weight: strata-change magnitude. $f(e) > 0$; larger when the transition activates/deactivates sovereignty dimensions (vertical moves) vs. lateral reconfiguration. | $\mathbb{R}^+$ |
| $g(n_e)$ | Repetition discount: $g$ is monotonically decreasing in $n_e$ (the number of times edge $e$ has been traversed). First traversal is most informative. | $(0, 1]$ |
| $\beta$ | Scaling coefficient | $\mathbb{R}^+$ |
6.3 Properties
- Static agent: $\pi = \emptyset \Rightarrow T(\pi) = 1$. An agent that never transitions has neutral edge value โ it neither gains nor loses from this term.
- Repetition decay: Traversing the same edge repeatedly yields diminishing returns. The functional form of $g$ is unspecified โ candidates include $g(n) = 1/n$, $g(n) = e^{-\gamma n}$, or $g(n) = 1/\ln(1+n)$. Empirical grounding is absent (see ยง7).
- Vertical premium: Transitions that change stratum (activating or deactivating sovereignty dimensions) are weighted more heavily than lateral moves within the same stratum. This reflects the intuition that changing capability is more informative than reconfiguring within fixed capability.
- Additivity: Edge values sum along the path. This assumes independence of sequential transitions โ a simplification that may not hold for paths with strong temporal correlation.
7. Open Questions and Falsifiability
The following are explicitly flagged as conjectures, ungrounded assumptions, or dependencies requiring external validation.
7.1 Conjectures
| ID | Claim | Current Status |
|---|---|---|
| C1 | The golden ratio $\varphi$ is the optimal protection-delegation ratio | Hypothesised from numerical optimisation; not derived from lattice geometry |
| C2 | $A(\tau)$ should be logarithmic | Chosen by analogy with trust dynamics; alternative forms (power-law, sigmoid) are plausible |
| C3 | Edge value $T(\pi)$ is additive over edges | Assumes transition independence; correlated paths may require a different aggregation |
| C4 | The 64-vertex lattice maps onto the UOR Foundation's toroidal algebraic structure | Structural correspondence observed; 96 vs 64 edge-count discrepancy unresolved |
| C5 | Sovereignty-class ZKP constraints yield ~3,000ร proof size reduction | Conjectured from lattice structure; requires formal circuit analysis |
7.2 Measurement Gaps
| ID | Term | Gap |
|---|---|---|
| M1 | $\sigma_{ij}$ (separation matrix entries) | No measurement methodology exists for the emergent forces (Reflect, Connect) |
| M2 | $f(e)$ (edge weights) | No empirical data on relative value of sovereignty transitions |
| M3 | $\beta, \alpha$ (scaling coefficients) | Require calibration against real agent systems |
| M4 | $\det(\Sigma)$ as aggregation | Determinant may not be the correct aggregation for multi-axis separation; trace, minimum eigenvalue, or other matrix norms are alternatives |
7.3 Breaking Conditions
The model's core claims weaken or fail if:
- UOR incompatibility: The 96 vs. 64 discrepancy reflects a structural mismatch rather than an edge-encoding feature โ geometric grounding weakens.
- Separation theorem violation: If dual-agent conditional independence cannot be maintained in practice with $\varepsilon < 0.1$ โ reconstruction ceiling $R < 1$ becomes impractical.
- Network effects are sublinear: If sovereignty coordination does not exhibit power-law returns โ the $(1 + \cdot)^k$ form overstates network value.
- Determinant pathology: If real sovereignty architectures cluster near singular $\Sigma$ matrices โ $\det(\Sigma)$ is numerically unstable and misleading.
8. Structural Properties
8.1 Multiplicative Gating
The model's multiplicative structure means any single term at zero eliminates total value:
$$\forall, \text{term}_i:; \text{term}_i = 0 \implies V(\pi, t) = 0$$
This is an intentional design property. It encodes the observation that privacy value requires simultaneous satisfaction of multiple conditions (cryptographic strength AND verifiability AND network effects AND architectural separation). Failure in any single dimension is catastrophic, not graceful.
Exception: The reconstruction difficulty $R(d) < 1$ is bounded away from both 0 and 1 under dual-agent separation, providing a proven floor.
8.2 Manifold Interpretation
When $V(\pi, t)$ is evaluated across all 64 vertices and their connecting edges, it defines a scalar field on the lattice. Under toroidal boundary conditions (if the UOR correspondence holds), this becomes a value field on a compact manifold with:
- Sources: High-stratum, high-separation vertices generating value
- Sinks: Low-stratum, entangled vertices extracting value
- Currents: Edges along which value flows, weighted by traversal frequency
The differential form โ $dV/dt = \nabla \cdot J(x, \dot{x}) + S(x) - D(x)$ โ is deferred to V5.
8.3 Surveillance Gap as Topology
The previously reported gap between sovereign and surveillance architectures (17รโ12,000ร depending on parameterisation) reinterprets under the manifold framing. Surveillance architectures are topologically constrained: activating protection breaks extraction pipelines, achieving separation requires architectural redesign. The gap is not arithmetic distance between two value points but the ratio of accessible manifold volume between two architectural classes.
9. Version Lineage
| Version | Date | Core Addition | Output Type |
|---|---|---|---|
| V1 | 2024 | $P \cdot C \cdot Q \cdot S$ | Static scalar |
| V2 | Oct 2025 | $e^{-\lambda t}$, $(1 + n/N_0)^k$ | Dynamic scalar |
| V3 | Nov 2025 | $R(d)$, $M(u,y)$, $\Phi(S,M)$ | Agent-aware scalar |
| V3.1 | Jan 2026 | $\sigma(\text{โฟป})^2$ | Architecture-gated scalar |
| V4 | Feb 2026 | $\Sigma$, $A(\tau)$, $T(\pi)$, $\Phi(\Sigma)$ | Manifold-aware scalar |
| V5 | โ | $dV/dt$ flow, differential form | Field on manifold |
10. Notation Summary
| Symbol | Meaning |
|---|---|
| $V(\pi, t)$ | Total privacy value for path $\pi$ at time $t$ |
| $P, C, Q, S$ | Privacy strength, credential verifiability, data quality, scope |
| $\lambda$ | Temporal decay rate |
| $\tau$ | Derivation chain (verified state transition history) |
| $A(\tau)$ | Temporal memory accumulation |
| $\alpha$ | Memory scaling coefficient |
| $h(\tau)$ | Derivation chain integrity fraction |
| $n_i$ | Agent count at stratum $i$ |
| $w_i$ | Stratum weight $= \binom{6}{i}/64$ |
| $N_0$ | Network baseline constant |
| $k$ | Network exponent |
| $R(d)$ | Reconstruction difficulty |
| $M(u,y)$ | Market maturity |
| $\Sigma$ | $4 \times 4$ separation matrix |
| $\sigma_{ij}$ | Pairwise separation coefficient between forces $i, j$ |
| $\varphi$ | Golden ratio $\approx 1.618$ |
| $\Phi(\Sigma)$ | Sovereignty duality term |
| $\pi$ | Path through sovereignty lattice |
| $T(\pi)$ | Edge value (trajectory term) |
| $f(e)$ | Edge weight function |
| $g(n_e)$ | Repetition discount function |
| $\beta$ | Edge value scaling coefficient |
References
- Travers, M. (2026). "Privacy is Value: From the Lattice Drake to the Manifold Dragon." Soul Sync.
- Travers, M. (2026). "Dual-Agent Privacy Architecture." Research Paper v3.8. agentprivacy-docs.
- Travers, M. (2026). "UOR ร 64-Tetrahedra ร ZK Mapping v1.0." agentprivacy-docs.
- Bergstra, J. & Burgess, M. (2019). Promise Theory: Principles and Applications.
- Drake, F. (1961). Drake Equation. Structural analogy: multiplicative gating of independent survival conditions.
- Shannon, C. (1948). "A Mathematical Theory of Communication." Information-theoretic bounds on reconstruction.
Citation
Travers, M. (2026). "Privacy Value Model V4: Formal Specification."
Working paper. https://github.com/mitchuski/agentprivacy-docs
This document presents the mathematics only. For narrative context, motivation, and the discovery process, see the companion piece: "Privacy is Value: From the Lattice Drake to the Manifold Dragon."
Peer review, critique, and falsification attempts are actively invited. Contact: mage@agentprivacy.ai
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