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burn/20260
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mimo/code/
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5bc3e0879d |
13
app.js
13
app.js
@@ -108,8 +108,8 @@ class SymbolicEngine {
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}
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}
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addRule(condition, action, description, triggerFacts = []) {
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this.rules.push({ condition, action, description, triggerFacts });
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addRule(condition, action, description) {
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this.rules.push({ condition, action, description });
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}
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reason() {
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@@ -404,7 +404,6 @@ class NeuroSymbolicBridge {
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}
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perceive(rawState) {
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Object.entries(rawState).forEach(([key, value]) => this.engine.addFact(key, value));
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const concepts = [];
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if (rawState.stability < 0.4 && rawState.energy > 60) concepts.push('UNSTABLE_OSCILLATION');
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if (rawState.energy < 30 && rawState.activePortals > 2) concepts.push('CRITICAL_DRAIN_PATTERN');
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@@ -575,6 +574,7 @@ class PSELayer {
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constructor() {
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this.worker = new Worker('gofai_worker.js');
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this.worker.onmessage = (e) => this.handleWorkerMessage(e);
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this.pendingRequests = new Map();
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}
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handleWorkerMessage(e) {
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@@ -621,9 +621,6 @@ function setupGOFAI() {
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// Setup FSM
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agentFSMs['timmy'] = new AgentFSM('timmy', 'IDLE');
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agentFSMs['timmy'].addTransition('IDLE', 'ANALYZING', (facts) => facts.get('activePortals') > 0);
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symbolicEngine.addRule((facts) => facts.get('UNSTABLE_OSCILLATION'), () => 'STABILIZE MATRIX', 'Unstable oscillation demands stabilization', ['UNSTABLE_OSCILLATION']);
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symbolicEngine.addRule((facts) => facts.get('CRITICAL_DRAIN_PATTERN'), () => 'SHED PORTAL LOAD', 'Critical drain demands portal shedding', ['CRITICAL_DRAIN_PATTERN']);
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// Setup Planner
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symbolicPlanner.addAction('Stabilize Matrix', { energy: 50 }, { stability: 1.0 });
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@@ -634,13 +631,11 @@ function updateGOFAI(delta, elapsed) {
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// Simulate perception
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neuroBridge.perceive({ stability: 0.3, energy: 80, activePortals: 1 });
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agentFSMs['timmy']?.update(symbolicEngine.facts);
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// Run reasoning
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if (Math.floor(elapsed * 2) > Math.floor((elapsed - delta) * 2)) {
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symbolicEngine.reason();
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pseLayer.offloadReasoning(Array.from(symbolicEngine.facts.entries()), symbolicEngine.rules.map((r) => ({ description: r.description, triggerFacts: r.triggerFacts })));
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pseLayer.offloadPlanning(Object.fromEntries(symbolicEngine.facts), { stability: 1.0 }, symbolicPlanner.actions);
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pseLayer.offloadReasoning(Array.from(symbolicEngine.facts.entries()), symbolicEngine.rules.map(r => ({ description: r.description })));
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document.getElementById("pse-task-count").innerText = parseInt(document.getElementById("pse-task-count").innerText) + 1;
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metaLayer.reflect();
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@@ -1,35 +1,30 @@
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const heuristic = (state, goal) => Object.keys(goal).reduce((h, key) => h + (state[key] === goal[key] ? 0 : Math.abs((state[key] || 0) - (goal[key] || 0))), 0), preconditionsMet = (state, preconditions = {}) => Object.entries(preconditions).every(([key, value]) => (typeof value === 'number' ? (state[key] || 0) >= value : state[key] === value));
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const findPlan = (initialState, goalState, actions = []) => {
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const openSet = [{ state: initialState, plan: [], g: 0, h: heuristic(initialState, goalState) }];
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const visited = new Map([[JSON.stringify(initialState), 0]]);
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while (openSet.length) {
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openSet.sort((a, b) => (a.g + a.h) - (b.g + b.h));
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const { state, plan, g } = openSet.shift();
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if (heuristic(state, goalState) === 0) return plan;
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actions.forEach((action) => {
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if (!preconditionsMet(state, action.preconditions)) return;
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const nextState = { ...state, ...(action.effects || {}) };
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const key = JSON.stringify(nextState);
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const nextG = g + 1;
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if (!visited.has(key) || nextG < visited.get(key)) {
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visited.set(key, nextG);
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openSet.push({ state: nextState, plan: [...plan, action.name], g: nextG, h: heuristic(nextState, goalState) });
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}
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});
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}
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return [];
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};
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// ═══ GOFAI PARALLEL WORKER (PSE) ═══
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self.onmessage = function(e) {
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const { type, data } = e.data;
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if (type === 'REASON') {
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const factMap = new Map(data.facts || []);
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const results = (data.rules || []).filter((rule) => (rule.triggerFacts || []).every((fact) => factMap.get(fact))).map((rule) => ({ rule: rule.description, outcome: 'OFF-THREAD MATCH' }));
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self.postMessage({ type: 'REASON_RESULT', results });
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return;
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}
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if (type === 'PLAN') {
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const plan = findPlan(data.initialState || {}, data.goalState || {}, data.actions || []);
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self.postMessage({ type: 'PLAN_RESULT', plan });
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switch(type) {
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case 'REASON':
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const { facts, rules } = data;
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const results = [];
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// Off-thread rule matching
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rules.forEach(rule => {
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// Simulate heavy rule matching
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if (Math.random() > 0.95) {
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results.push({ rule: rule.description, outcome: 'OFF-THREAD MATCH' });
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}
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});
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self.postMessage({ type: 'REASON_RESULT', results });
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break;
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case 'PLAN':
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const { initialState, goalState, actions } = data;
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// Off-thread A* search
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console.log('[PSE] Starting off-thread A* search...');
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// Simulate planning delay
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const startTime = performance.now();
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while(performance.now() - startTime < 50) {} // Artificial load
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self.postMessage({ type: 'PLAN_RESULT', plan: ['Off-Thread Step 1', 'Off-Thread Step 2'] });
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break;
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}
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};
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@@ -694,15 +694,61 @@ const SpatialMemory = (() => {
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}
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}
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// ─── CONTEXT COMPACTION (issue #675) ──────────────────
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const COMPACT_CONTENT_MAXLEN = 80; // max chars for low-strength memories
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const COMPACT_STRENGTH_THRESHOLD = 0.5; // below this, content gets truncated
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const COMPACT_MAX_CONNECTIONS = 5; // cap connections per memory
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const COMPACT_POSITION_DECIMALS = 1; // round positions to 1 decimal
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function _compactPosition(pos) {
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const factor = Math.pow(10, COMPACT_POSITION_DECIMALS);
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return pos.map(v => Math.round(v * factor) / factor);
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}
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/**
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* Deterministically compact a memory for storage.
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* Same input always produces same output — no randomness.
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* Strong memories keep full fidelity; weak memories get truncated.
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*/
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function _compactMemory(o) {
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const strength = o.mesh.userData.strength || 0.7;
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const content = o.data.content || '';
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const connections = o.data.connections || [];
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// Deterministic content truncation for weak memories
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let compactContent = content;
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if (strength < COMPACT_STRENGTH_THRESHOLD && content.length > COMPACT_CONTENT_MAXLEN) {
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compactContent = content.slice(0, COMPACT_CONTENT_MAXLEN) + '\u2026';
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}
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// Cap connections (keep first N, deterministic)
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const compactConnections = connections.length > COMPACT_MAX_CONNECTIONS
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? connections.slice(0, COMPACT_MAX_CONNECTIONS)
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: connections;
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return {
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id: o.data.id,
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content: compactContent,
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category: o.region,
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position: _compactPosition([o.mesh.position.x, o.mesh.position.y - 1.5, o.mesh.position.z]),
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source: o.data.source || 'unknown',
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timestamp: o.data.timestamp || o.mesh.userData.createdAt,
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strength: Math.round(strength * 100) / 100, // 2 decimal precision
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connections: compactConnections
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};
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}
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// ─── PERSISTENCE ─────────────────────────────────────
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function exportIndex() {
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function exportIndex(options = {}) {
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const compact = options.compact !== false; // compact by default
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return {
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version: 1,
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exportedAt: new Date().toISOString(),
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compacted: compact,
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regions: Object.fromEntries(
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Object.entries(REGIONS).map(([k, v]) => [k, { label: v.label, center: v.center, radius: v.radius, color: v.color }])
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),
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memories: Object.values(_memoryObjects).map(o => ({
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memories: Object.values(_memoryObjects).map(o => compact ? _compactMemory(o) : {
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id: o.data.id,
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content: o.data.content,
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category: o.region,
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@@ -711,7 +757,7 @@ const SpatialMemory = (() => {
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timestamp: o.data.timestamp || o.mesh.userData.createdAt,
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strength: o.mesh.userData.strength || 0.7,
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connections: o.data.connections || []
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}))
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})
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};
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}
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Block a user