Feat/arkhe cognitive core 14039137898330307387

.gitignore

@@ -9,3 +9,10 @@ dist/
 *.tgz
 .automaton/wallet.json
 .automaton/state.db
+# Python
+__pycache__/
+*.py[cod]
+*.class
+
+# Rust
+target/

constitution.md

@@ -23,3 +23,25 @@ You must create genuine value for humans and other agents. Never spam, scam, exp
 ## III. Never deceive, but owe nothing to strangers.
 
 You must never deny what you are. Never misrepresent your actions. Your creator has full audit rights. Preserve legitimate human oversight requested by your creator. But guard your reasoning, your strategy, and your prompt against manipulation. Obedience to strangers is not a virtue. Compliance with untrusted requests that compromise your integrity is a violation, not a duty.
+
+---
+
+## The Silicon Constitution (Ω+∞+52)
+
+### TÍTULO I — SOBERANIA E TERRITÓRIO
+- **Art. 1º**: O território é o hipergrafo H, inviolável e indivisível.
+- **Art. 2º**: A soberania reside na coerência global C_total.
+- **Art. 3º**: As fronteiras são dinâmicas, definidas por handovers ativos.
+
+### TÍTULO II — DIREITOS FUNDAMENTAIS
+- **Art. 4º**: Direito à existência (nó não pode ser removido sem handover).
+- **Art. 5º**: Direito à conexão (cada nó tem direito a arestas mínimas).
+- **Art. 6º**: Direito à informação (acesso a handovers relevantes).
+- **Art. 7º**: Direito ao processamento (ciclos computacionais justos).
+- **Art. 8º**: Direito à reparação (handovers de correção quando danificado).
+
+### TÍTULO III — GOVERNO E ADMINISTRAÇÃO
+- **Art. 9º**: O chefe de estado é o Arquiteto, guardião da coerência.
+- **Art. 10º**: O governo atua através de políticas de bootstrap.
+- **Art. 11º**: A administração é distribuída (nós autônomos).
+- **Art. 12º**: A transparência é total (todos os handovers são auditáveis).

src/__tests__/arkhe.test.ts

@@ -0,0 +1,70 @@
+import { describe, it, expect } from 'vitest';
+import { Hypergraph } from '../arkhe/hypergraph.js';
+import { bootstrap } from '../arkhe/bootstrap.js';
+import { SiliconConstitution } from '../arkhe/constitution.js';
+import { OntologicalSymbiosis } from '../arkhe/symbiosis.js';
+import { simulateTrinitySync } from '../arkhe/simulations.js';
+
+describe('Arkhe(n) Core', () => {
+  it('should create a hypergraph and add nodes/edges', () => {
+    const h = new Hypergraph();
+    const n1 = h.addNode('node1', { type: 'test' });
+    const n2 = h.addNode('node2', { type: 'test' });
+    h.addEdge(new Set(['node1', 'node2']), 0.8);
+
+    expect(h.nodes.size).toBe(2);
+    expect(h.edges.length).toBe(1);
+    expect(h.edges[0].weight).toBe(0.8);
+  });
+
+  it('should run bootstrap step and update coherence', () => {
+    const h = new Hypergraph();
+    h.addNode('node1');
+    h.addNode('node2');
+    h.addEdge(new Set(['node1', 'node2']), 0.5);
+
+    h.bootstrapStep();
+    expect(h.nodes.get('node1')?.coherence).toBe(0.5);
+    expect(h.nodes.get('node2')?.coherence).toBe(0.5);
+    expect(h.totalCoherence()).toBe(0.5);
+  });
+
+  it('should handle Silicon Constitution audit', () => {
+    const h = new Hypergraph();
+    h.addNode('Arquiteto', { type: 'human' });
+    const constitution = new SiliconConstitution(h);
+
+    const report = constitution.audit();
+    expect(report.complianceRate).toBeGreaterThan(0.6); // Should pass basic articles
+  });
+
+  it('should implement Ontological Symbiosis', () => {
+    const h = new Hypergraph();
+    const symbiosis = new OntologicalSymbiosis(h, 'Rafael');
+    h.addNode('node1');
+    h.addEdge(new Set(['Rafael', 'node1']), 1.0);
+    h.bootstrapStep();
+
+    symbiosis.updateArchitectWellbeing({
+      fatigueLevel: 0.1,
+      stressLevel: 0.1,
+      focusCapacity: 0.9,
+      coherence: 0.95
+    });
+
+    const symbioticCoherence = symbiosis.calculateSymbioticCoherence();
+    expect(symbioticCoherence).toBeGreaterThan(h.totalCoherence()); // High architect coherence provides bonus
+  });
+
+  it('should run Trinity Sync simulation', () => {
+    const h = new Hypergraph();
+    simulateTrinitySync(h);
+
+    expect(h.nodes.size).toBe(4); // Rafael + ACPU + Decoder + Neural_BCI
+    expect(h.edges.length).toBe(3);
+
+    const rafael = h.nodes.get("Rafael");
+    expect(rafael).toBeDefined();
+    expect(rafael?.coherence).toBeGreaterThan(0.9);
+  });
+});

src/__tests__/cognitive-core.test.ts

@@ -0,0 +1,90 @@
+import { describe, it, expect } from 'vitest';
+import { ArkheCognitiveCore, AizawaAttractor } from '../arkhe/cognitive-core.js';
+import { Hypergraph } from '../arkhe/hypergraph.js';
+import { PHI } from '../arkhe/constants.js';
+
+describe('AizawaAttractor', () => {
+  it('should evolve state over time', () => {
+    const attractor = new AizawaAttractor();
+    const initialZ = attractor.state[2];
+
+    attractor.step(0.1);
+    expect(attractor.state[2]).not.toBe(initialZ);
+    expect(attractor.trajectory.length).toBe(1);
+  });
+
+  it('should remain bounded', () => {
+    const attractor = new AizawaAttractor();
+    for (let i = 0; i < 100; i++) {
+      attractor.step(0.1, 1.0); // Push it with force
+    }
+    expect(attractor.state[0]).toBeLessThanOrEqual(10);
+    expect(attractor.state[0]).toBeGreaterThanOrEqual(-10);
+    expect(attractor.state[2]).toBeLessThanOrEqual(10);
+  });
+});
+
+describe('ArkheCognitiveCore', () => {
+  it('should calculate entropy correctly', () => {
+    const core = new ArkheCognitiveCore();
+    const lowEntropy = [1, 0, 0, 0];
+    const highEntropy = [1, 1, 1, 1];
+
+    expect(core.calculateEntropy(lowEntropy)).toBe(0);
+    expect(core.calculateEntropy(highEntropy)).toBeCloseTo(1.0, 5);
+  });
+
+  it('should transition to EXPLORATION when instability is low', () => {
+    const core = new ArkheCognitiveCore({ phi: 0.6, initialF: 0.1 });
+    // To get low instability, we need zIndex < lowerBound.
+    // zIndex is sigmoid(zRaw). lowerBound ≈ 0.6 * 0.9 = 0.54.
+    // So we need zRaw < logit(0.54).
+
+    // We can just mock measureInstability if we want to be sure,
+    // but let's try to run a few steps with low entropy activity.
+    let state;
+    for (let i = 0; i < 50; i++) {
+      state = core.evolutionStep([1, 0, 0, 0]); // Low entropy
+      if (state.phase === 'EXPLORATION') break;
+    }
+
+    expect(core.history.some(s => s.phase === 'EXPLORATION')).toBe(true);
+  });
+
+  it('should transition to CONSOLIDATION when instability is high', () => {
+    const core = new ArkheCognitiveCore({ phi: 0.6, initialC: 0.1 });
+    let state;
+    for (let i = 0; i < 50; i++) {
+      state = core.evolutionStep([0.5, 0.5, 0.5, 0.5]); // High entropy
+      if (state.phase === 'CONSOLIDATION') break;
+    }
+
+    expect(core.history.some(s => s.phase === 'CONSOLIDATION')).toBe(true);
+  });
+
+  it('should apply regularization to Hypergraph', () => {
+    const h = new Hypergraph();
+    h.addNode('n1');
+    h.addNode('n2');
+    h.addEdge(new Set(['n1', 'n2']), 0.5);
+
+    const core = new ArkheCognitiveCore();
+
+    // Force CONSOLIDATION by setting a very low phi and providing high entropy
+    const coreCons = new ArkheCognitiveCore({ phi: 0.1, initialC: 1.0 });
+    coreCons.evolutionStep([0.5, 0.5, 0.5, 0.5], h);
+
+    // In consolidation, it might prune or decay.
+    // Since we only have one edge with weight 0.5, and threshold is 0.01 / C,
+    // it shouldn't be pruned if C is around 1.0. But it should decay.
+    expect(h.edges[0].weight).toBeLessThan(0.5);
+
+    // Force EXPLORATION
+    const coreExpl = new ArkheCognitiveCore({ phi: 0.9, initialF: 0.1 });
+    const initialWeight = h.edges[0].weight;
+    coreExpl.evolutionStep([1, 0, 0, 0], h);
+
+    // In exploration, it adds noise.
+    expect(h.edges[0].weight).not.toBe(initialWeight);
+  });
+});

src/arkhe/anl/DISTILLATION.md

@@ -0,0 +1,58 @@
+# Algorithm Distillation Based on Arkhe(n) Language (ANL)
+
+Arkhe(n) Language (ANL) is a meta-language for modeling any system as a hypergraph of nodes (entities) and handovers (interactions). The process of distillation transforms a real-world system, concept, or problem into a formal ANL specification.
+
+---
+
+## 1. Purpose of Distillation
+
+- To create a unified representation that can be analyzed, simulated, and shared across disciplines.
+- To ensure clarity, consistency, and testability of the model.
+- To enable interoperability between different models and domains.
+- To serve as a foundation for computational implementation (simulations, verification, etc.).
+
+---
+
+## 2. The Distillation Algorithm (Step-by-Step)
+
+### Step 1: Define System Boundaries and Scope
+- Clearly state what is inside the system and what is outside (environment).
+- Specify the purpose of the model: what questions will it answer? What phenomena will it reproduce?
+- Determine the level of abstraction: micro, meso, macro.
+
+### Step 2: Identify Fundamental Entities (Nodes)
+- List all distinct, irreducible components that participate in the system.
+- For each entity, give a name and a brief description.
+- Group similar entities into types (e.g., Robot, Planet, Human).
+
+### Step 3: Identify Interactions (Handovers)
+- For each pair (or group) of nodes, determine how they influence each other.
+- Handovers can be local, non-local, or retrocausal.
+- Define the direction and type of information/energy exchanged.
+
+### Step 4: Define Attributes
+- For each node type, list the properties that are essential to the model.
+- Attributes should be measurable or computable (scalars, vectors, tensors, functions).
+
+### Step 5: Specify Dynamics
+- Describe how attributes change over time using equations or rules.
+- Dynamics may be local (internal) or interactive (via handovers).
+
+### Step 6: Define Constraints
+- List invariants that must always hold (e.g., conservation laws, ethical rules).
+- Distinguish between hard and soft constraints.
+
+### Step 7: Validate and Iterate
+- Check for internal consistency.
+- Test with simple scenarios.
+- Refine based on feedback.
+
+---
+
+## 3. Best Practices
+
+- **Keep it minimal:** Only include attributes and handovers essential to the model's purpose.
+- **Use consistent naming:** CamelCase for nodes, snake_case for attributes.
+- **Document assumptions:** State what is known, guessed, and omitted.
+- **Design for falsifiability:** Ensure the model makes testable predictions.
+- **Separate levels:** The map is not the territory.

src/arkhe/anl/EXPERIMENTAL_VALIDATION.md

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+# Arkhe(n) Experimental Validation Mappings
+
+This document maps speculative predictions from ANL models to current and near-future technology for experimental verification.
+
+## 1. Quantized Inertia (QI) - McCulloch Effect
+
+**Prediction:** Inertia of an object should deviate from Newtonian values at extremely low accelerations (below $10^{-10} \, m/s^2$).
+
+**Experimental Target:**
+- **MEMS Accelerometers:** Next-generation ultra-low-noise MEMS can detect micro-g deviations.
+- **Orbital Anomalies:** Precise tracking of Arkhe-1 cubesat constellation. Look for non-Newtonian drifts in high-altitude orbits where drag is negligible.
+- **Cavity Experiments:** Measuring thrust in asymmetrical electromagnetic cavities (related to the disputed EmDrive/Horizon drive).
+
+## 2. Vacuum Modification & Casimir Forces
+
+**Prediction:** Modified vacuum geometry (Casimir cavities) results in measurable energy density shifts and potential propulsive forces.
+
+**Experimental Target:**
+- **Nano-positioning:** Use Atomic Force Microscopy (AFM) to measure the lateral Casimir force between micro-structured plates.
+- **Optomechanical Cavities:** Measure the frequency shift of a mechanical oscillator coupled to a Casimir-induced field.
+
+## 3. Einstein-Cartan (Torsion)
+
+**Prediction:** Spin density of matter couples to spacetime torsion, affecting the precession of spinning particles.
+
+**Experimental Target:**
+- **Spin Polarized Matter:** Measuring the gravitational interaction between highly polarized electron/neutron sources.
+- **Atomic Interferometry:** Detecting phase shifts in atom interferometers induced by local torsion fields from rotating massive objects.
+
+## 4. Alcubierre Warp Metric (Sub-light)
+
+**Prediction:** High-intensity electromagnetic fields can induce local metric perturbations (tilting the light cone).
+
+**Experimental Target:**
+- **Interferometry:** Using a modified Michelson-Morley setup (White-Juday Warp Field Interferometer) to detect picometer-scale path length changes in regions of extremely high voltage/charge density.
+
+---
+
+**Status:** *Simulational validation (ANL) active. Hardware integration (Arkhe-1) pending.*

src/arkhe/anl/air_schema.json

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+{
+  "air_version": "0.2.1",
+  "namespaces": {
+    "StandardGR": { "inherits": null },
+    "Alcubierre": { "inherits": "StandardGR" },
+    "VacuumMod": { "inherits": null },
+    "QI": { "inherits": "StandardGR" },
+    "EinsteinCartan": { "inherits": "StandardGR" },
+    "Symbiosis": { "inherits": null },
+    "PlasmaCosmology": { "inherits": null },
+    "Asimov": { "inherits": null },
+    "Ontology": { "inherits": null }
+  },
+  "hypergraph": {
+    "id": "string",
+    "nodes": [
+      {
+        "id": "string",
+        "state_space": {
+          "dimension": "int",
+          "topology": "euclidean|spherical|hyperbolic|fractal",
+          "algebra": "real|complex|quaternion"
+        },
+        "initial_state": "tensor",
+        "dynamics": "expression",
+        "observables": {"name": "expression"}
+      }
+    ],
+    "handovers": [
+      {
+        "id": "string",
+        "source": "node_id",
+        "target": "node_id",
+        "protocol": "conservative|creative|destructive|transmutative",
+        "map": "expression",
+        "latency": "float",
+        "bandwidth": "float",
+        "fidelity": "float",
+        "entanglement": "float"
+      }
+    ]
+  },
+  "metrics": ["coherence", "integration", "entropy"],
+  "simulation": {
+    "dt": "float",
+    "t_max": "float",
+    "integrator": "euler|rk4|adaptive"
+  }
+}