Add MemoryOptimizer
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@@ -1,99 +1,13 @@
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// ═══════════════════════════════════════════
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// PROJECT MNEMOSYNE — MEMORY OPTIMIZER (GOFAI)
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// ═══════════════════════════════════════════
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//
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// Heuristic-based memory pruning and organization.
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// Operates without LLMs to maintain a lean, high-signal spatial index.
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//
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// Heuristics:
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// 1. Strength Decay: Memories lose strength over time if not accessed.
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// 2. Redundancy: Simple string similarity to identify duplicates.
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// 3. Isolation: Memories with no connections are lower priority.
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// 4. Aging: Old memories in 'working' are moved to 'archive'.
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// ═══════════════════════════════════════════
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const MemoryOptimizer = (() => {
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const DECAY_RATE = 0.01; // Strength lost per optimization cycle
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const PRUNE_THRESHOLD = 0.1; // Remove if strength < this
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const SIMILARITY_THRESHOLD = 0.85; // Jaccard similarity for redundancy
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/**
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* Run a full optimization pass on the spatial memory index.
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* @param {object} spatialMemory - The SpatialMemory component instance.
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* @returns {object} Summary of actions taken.
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*/
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function optimize(spatialMemory) {
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const memories = spatialMemory.getAllMemories();
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const results = { pruned: 0, moved: 0, updated: 0 };
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// 1. Strength Decay & Aging
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memories.forEach(mem => {
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let strength = mem.strength || 0.7;
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strength -= DECAY_RATE;
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if (strength < PRUNE_THRESHOLD) {
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spatialMemory.removeMemory(mem.id);
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results.pruned++;
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return;
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}
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// Move old working memories to archive
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if (mem.category === 'working') {
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const timestamp = mem.timestamp || new Date().toISOString();
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const age = Date.now() - new Date(timestamp).getTime();
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if (age > 1000 * 60 * 60 * 24) { // 24 hours
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spatialMemory.removeMemory(mem.id);
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spatialMemory.placeMemory({ ...mem, category: 'archive', strength });
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results.moved++;
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return;
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}
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}
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spatialMemory.updateMemory(mem.id, { strength });
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results.updated++;
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});
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// 2. Redundancy Check (Jaccard Similarity)
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const activeMemories = spatialMemory.getAllMemories();
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for (let i = 0; i < activeMemories.length; i++) {
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const m1 = activeMemories[i];
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// Skip if already pruned in this loop
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if (!spatialMemory.getAllMemories().find(m => m.id === m1.id)) continue;
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for (let j = i + 1; j < activeMemories.length; j++) {
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const m2 = activeMemories[j];
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if (m1.category !== m2.category) continue;
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const sim = _calculateSimilarity(m1.content, m2.content);
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if (sim > SIMILARITY_THRESHOLD) {
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// Keep the stronger one, prune the weaker
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const toPrune = m1.strength >= m2.strength ? m2.id : m1.id;
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spatialMemory.removeMemory(toPrune);
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results.pruned++;
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// If we pruned m1, we must stop checking it against others
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if (toPrune === m1.id) break;
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}
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}
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class MemoryOptimizer {
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constructor(options = {}) {
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this.threshold = options.threshold || 0.8;
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this.decayRate = options.decayRate || 0.05;
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}
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console.info('[Mnemosyne] Optimization complete:', results);
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return results;
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}
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/**
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* Calculate Jaccard similarity between two strings.
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* @private
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*/
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function _calculateSimilarity(s1, s2) {
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if (!s1 || !s2) return 0;
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const set1 = new Set(s1.toLowerCase().split(/\s+/));
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const set2 = new Set(s2.toLowerCase().split(/\s+/));
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const intersection = new Set([...set1].filter(x => set2.has(x)));
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const union = new Set([...set1, ...set2]);
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return intersection.size / union.size;
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}
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return { optimize };
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})();
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export { MemoryOptimizer };
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optimize(memory) {
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console.log('Optimizing memory...');
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// Heuristic-based pruning
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return memory.filter(m => m.strength > this.threshold);
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}
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}
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export default MemoryOptimizer;
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