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https://github.com/Youzini-afk/ST-Bionic-Memory-Ecology.git
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115 lines
3.7 KiB
JavaScript
115 lines
3.7 KiB
JavaScript
// ST-BME: 记忆动力学模块
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// 实现访问强化、时间衰减、混合评分 — 来自 PeroCore 的核心创新
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/**
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* 访问强化：节点被召回/注入时调用
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* - accessCount += 1
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* - importance += 0.1（上限 10）
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* - lastAccessTime 更新
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*
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* @param {object} node
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*/
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export function reinforceAccess(node) {
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node.accessCount = (node.accessCount || 0) + 1;
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node.importance = Math.min(10, (node.importance || 5) + 0.1);
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node.lastAccessTime = Date.now();
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}
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/**
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* 计算时间衰减因子
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* 使用对数衰减（PeroCore 方式）而非指数衰减：
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* factor = 0.8 + 0.2 / (1 + ln(1 + Δt_days))
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*
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* 特点：久远但重要的记忆不会快速消失
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* - Δt = 0天 → factor = 1.0
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* - Δt = 1天 → factor ≈ 0.93
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* - Δt = 7天 → factor ≈ 0.89
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* - Δt = 30天 → factor ≈ 0.85
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* - Δt = 365天 → factor ≈ 0.83
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*
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* @param {number} createdTime - 创建时间戳(ms)
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* @param {number} [now] - 当前时间戳(ms)
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* @returns {number} 衰减因子 [0.8, 1.0]
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*/
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export function timeDecayFactor(createdTime, now = Date.now()) {
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const deltaDays = Math.max(0, (now - createdTime) / (1000 * 60 * 60 * 24));
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return 0.8 + 0.2 / (1 + Math.log(1 + deltaDays));
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}
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/**
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* 混合评分公式
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* FinalScore = (GraphScore×α + VecScore×β + ImportanceNorm×γ) × TimeDecay
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*
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* 默认权重：α=0.6, β=0.3, γ=0.1
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*
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* @param {object} params
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* @param {number} params.graphScore - 图扩散能量得分 [0, 2]
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* @param {number} params.vectorScore - 向量相似度 [0, 1]
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* @param {number} params.importance - 节点重要性 [0, 10]
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* @param {number} params.createdTime - 节点创建时间
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* @param {object} [weights] - 权重配置
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* @returns {number} 最终得分
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*/
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export function hybridScore({
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graphScore = 0,
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vectorScore = 0,
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lexicalScore = 0,
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importance = 5,
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createdTime = Date.now(),
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}, weights = {}) {
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const alpha = weights.graphWeight ?? 0.6;
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const beta = weights.vectorWeight ?? 0.3;
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const gamma = weights.importanceWeight ?? 0.1;
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const delta = weights.lexicalWeight ?? 0;
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// 归一化
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const normGraph = Math.max(0, Math.min(1, graphScore / 2.0)); // PEDSA 能量范围 [-2, 2] → [0, 1]
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const normVec = Math.max(0, Math.min(1, vectorScore));
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const normLexical = Math.max(0, Math.min(1, lexicalScore));
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const normImportance = Math.max(0, Math.min(1, importance / 10.0));
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const totalWeight = Math.max(
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1e-6,
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Math.max(0, alpha) + Math.max(0, beta) + Math.max(0, gamma) + Math.max(0, delta),
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);
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const baseScore =
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(normGraph * alpha +
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normVec * beta +
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normLexical * delta +
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normImportance * gamma) /
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totalWeight;
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const decay = timeDecayFactor(createdTime);
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return baseScore * decay;
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}
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/**
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* 边权衰减：长期未被激活的边降低强度
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* 只降低到最低 0.1，不会归零
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*
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* @param {object[]} edges
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* @param {Set<string>} activatedEdgeIds - 最近被激活（出现在扩散路径上）的边 ID
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* @param {number} [decayRate=0.02] - 每次调用的衰减量
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*/
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export function decayEdgeWeights(edges, activatedEdgeIds = new Set(), decayRate = 0.02) {
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for (const edge of edges) {
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if (activatedEdgeIds.has(edge.id)) {
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// 被激活的边轻微加强
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edge.strength = Math.min(1.0, edge.strength + decayRate * 0.5);
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} else {
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// 未被激活的边轻微衰减
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edge.strength = Math.max(0.1, edge.strength - decayRate);
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}
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}
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}
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/**
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* 批量对选中节点执行访问强化
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* @param {object[]} nodes - 被召回的节点列表
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*/
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export function reinforceAccessBatch(nodes) {
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for (const node of nodes) {
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reinforceAccess(node);
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}
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}
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