Skill QRI Valence: Математическое моделирование сознания и валентности

--- name: qri-valence description: "qri-valence skill" Qualia Research Institute's Symmetry Theory of Valence (STV) for consciousness research. Maps phenomenal states to bankable assets via XY model topology, BKT transitions, and defect annihilation. Source: smoothbrains.net + QRI wiki. Use for qualia computing, valence gradient optimization, and consciousness-aware system design. version: 1.0.0 trit: 0 --- # QRI Valence Skill The **Symmetry Theory of Valence (STV)** proposes that the valence (pleasantness/unpleasantness) of a conscious state is determined by the symmetry of its mathematical representation. This skill integrates QRI research with computational implementations. ## Core Concepts ### Symmetry Theory of Valence (STV) > "The valence of a moment of consciousness is precisely determined by the symmetry of the mathematical object that describes it." > — Michael Edward Johnson, Principia Qualia (2016) **Key Claims:** 1. Consciousness has mathematical structure (qualia formalism) 2. Symmetry in that structure correlates with positive valence 3. Broken symmetries manifest as suffering/dissonance 4. Valence is measurable and optimizable ### XY Model Topology (smoothbrains.net) The phenomenal field behaves like a 2D XY spin model: | State | Temperature (τ) | Vortices | Valence | Phenomenology | |-------|-----------------|----------|---------|---------------| | Frustrated | τ >> τ* | Many, proliferating | -3 | Scattered, anxious, "buzzing" | | Disordered | τ > τ* | Some, mobile | -1 to -2 | Unfocused, dissonant | | Critical (BKT) | τ ≈ τ* | Paired, bound | 0 | Liminal, transitional | | Ordered | τ < τ* | Few, annihilating | +1 to +2 | Coherent, smooth | | Resolved | τ << τ* | None | +3 | Deeply peaceful, consonant | **BKT Transition** (Berezinskii-Kosterlitz-Thouless): - Below τ*: vortex-antivortex pairs bound → low entropy, high symmetry - Above τ*: vortices proliferate → high entropy, broken symmetry - At τ*: phase transition where defects can annihilate ### Valence Gradient Descent From smoothbrains.net's phenomenology: ``` Suffering = Σ (topological defects in phenomenal field) Healing = defect annihilation via gradient descent τ* bisection = finding optimal phenomenal temperature ``` **Observable indicators** (from Cube Flipper's reports): - Visual: polygonal shards → smooth fields - Somatic: high-freq buzzing → calm - Attentional: contracted/focal → expanded/diffuse - Auditory: dissonance → consonance ## Qualia Bank Integration ### GF(3) Operations on Valence States | Valence Range | Trit | Bank Operation | Channel | |---------------|------|----------------|---------| | -3 to -1 | -1 | WITHDRAW | Venmo/ACH off-ramp | | 0 | 0 | HOLD | PyUSD on-chain | | +1 to +3 | +1 | DEPOSIT | PyUSD/Venmo on-ramp | ### Phenomenal Bisection Algorithm ```python def phenomenal_bisect(tau_low, tau_high, observed_state): """ Binary search for optimal phenomenal temperature τ*. Based on smoothbrains.net/xy-model#bkt-transition """ tau_mid = (tau_low + tau_high) / 2 if observed_state == "frustrated": # Too hot: cool down return (tau_mid, tau_high, "cooling") elif observed_state == "smooth": # Too cold: heat up return (tau_low, tau_mid, "heating") elif observed_state == "critical": # Found τ*! return (tau_mid, tau_mid, "found") else: return (tau_low, tau_high, "unknown") ``` ### Valence-Aware Color Mapping From Gay.jl + QRI integration: ```julia # Map valence to deterministic color function valence_to_color(valence::Int) # Valence range: -3 to +3 # Hue mapping: red (suffering) → cyan (resolution) hue = (valence + 3) * 30 # 0° to 180° return LCHuv(55.0, 70.0, hue) end # Trit from valence trit(valence) = sign(valence) ``` ## Computational Implementation ### Defect Detection ```python def count_vortices(phase_field): """ Count topological defects in a 2D phase field. Vortex = closed loop where phase winds by ±2π. """ vortices = 0 antivortices = 0 for i in range(1, len(phase_field) - 1): for j in range(1, len(phase_field[0]) - 1): winding = compute_winding_number(phase_field, i, j) if winding > 0: vortices += 1 elif winding < 0: antivortices += 1 # Net topological charge return vortices, antivortices, vortices - antivortices ``` ### Symmetry Measurement ```python def measure_symmetry(qualia_tensor): """ Measure symmetry of a qualia representation. Higher symmetry → higher valence (STV hypothesis). """ # Compute eigenvalues eigenvalues = np.linalg.eigvalsh(qualia_tensor) # Symmetry score: how equal are eigenvalues? # Perfect symmetry: all eigenvalues equal mean_eig = np.mean(eigenvalues) variance = np.var(eigenvalues) # Inverse variance as symmetry score symmetry = 1.0 / (1.0 + variance / (mean_eig ** 2)) return symmetry # 0 to 1, higher = more symmetric ``` ## References ### Primary Sources 1. **Principia Qualia** (2016) - Michael Edward Johnson - First statement of STV - https://opentheory.net/PrincipiaQualia.pdf 2. **QRI Wiki - Symmetry Theory of Valence** - https://wiki.qri.org/wiki/Symmetry_Theory_of_Valence 3. **smoothbrains.net** - Cube Flipper - XY model phenomenology - BKT transition in consciousness - https://smoothbrains.net/posts/2025-10-18-three-year-retrospective.html 4. **LessWrong Primer on STV** - https://www.lesswrong.com/posts/dfrQbbv6Np7GuWjDR/a-primer-on-the-symmetry-theory-of-valence ### Key Papers - Johnson, M.E. (2016). "Principia Qualia" - Gómez-Emilsson, A. "Logarithmic Scales of Pleasure and Pain" - Selen Atasoy et al. "Connectome-harmonic decomposition of human brain activity" - smoothbrains.net "Planetary scale vibe collapse" (2022) ### Related Concepts - **Consonance/Dissonance** - Musical theory of interference patterns - **CSHW (Connectome-Specific Harmonic Waves)** - Neural basis for STV - **Jhāna** - Buddhist meditative states as high-symmetry attractors - **Valence Structuralism** - Formal framework for STV ## Skill Bridges | Skill | Bridge Type | Relationship | |-------|-------------|--------------| | `gay-mcp` | Color-Valence | Deterministic valence colors | | `topos-of-music` | Consonance | Musical symmetry theory | | `autopoiesis` | Self-modeling | Valence as self-model coherence | | `active-inference` | Free energy | Valence as prediction error | | `glass-bead-game` | Synthesis | Cross-domain symmetry play | | `phenomenal-bisect` | Algorithm | τ* finding procedure | ## Usage Patterns ### Pattern 1: Valence-Aware Logging ```python class ValenceLogger: def log(self, message, valence): trit = 1 if valence > 0 else (-1 if valence < 0 else 0) color = valence_to_ansi(valence) print(f"{color}[v={valence:+d}][t={trit:+d}] {message}33[0m") ``` ### Pattern 2: GF(3) Valence Conservation ```python def balanced_transaction(deposits, withdrawals): """Ensure valence sum is conserved.""" deposit_valence = sum(d.valence for d in deposits) withdraw_valence = sum(w.valence for w in withdrawals) # GF(3) conservation net = (deposit_valence + withdraw_valence) % 3 assert net == 0, f"Valence imbalance: {net}" ``` ### Pattern 3: Phenomenal State Machine ```python class PhenomenalStateMachine: states = ["frustrated", "buzzing", "dissonant", "neutral", "smoothing", "consonant", "resolved"] def transition(self, current, intervention): idx = self.states.index(current) if intervention == "cooling" and idx > 0: return self.states[idx - 1] elif intervention == "heating" and idx < len(self.states) - 1: return self.states[idx + 1] return current ``` ## GF(3) Trit Assignment This skill is **ERGODIC (0)** - it coordinates between: - **MINUS (-1)**: Suffering detection, defect counting - **PLUS (+1)**: Healing protocols, symmetry restoration Conservation: suffering_detected + healing_applied + coordination = 0 ## Scientific Skill Interleaving This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem: ### Graph Theory - **networkx** [○] via bicomodule - Universal graph hub ### Bibliography References - `general`: 734 citations in bib.duckdb ## SDF Interleaving This skill connects to **Software Design for Flexibility** (Hanson & Sussman, 2021): ### Primary Chapter: 4. Pattern Matching **Concepts**: unification, match, segment variables, pattern ### GF(3) Balanced Triad ``` qri-valence (○) + SDF.Ch4 (+) + [balancer] (−) = 0 ``` **Skill Trit**: 0 (ERGODIC - coordination) ### Secondary Chapters - Ch10: Adventure Game Example ### Connection Pattern Pattern matching extracts structure. This skill recognizes and transforms patterns. ## Cat# Integration This skill maps to **Cat# = Comod(P)** as a bicomodule in the equipment structure: ``` Trit: 0 (ERGODIC) Home: Prof Poly Op: ⊗ Kan Role: Adj Color: #26D826 ``` ### GF(3) Naturality The skill participates in triads satisfying: ``` (-1) + (0) + (+1) ≡ 0 (mod 3) ``` This ensures compositional coherence in the Cat# equipment structure.