Charles Mordelet

371  for (let iter = 0; iter < cfg.maxIter; iter++) {372    iterations++373    const prev = new Map(beliefs)374375    // ── Dynamic affinityScale from convergence rate ───────────────────376    // rawRatio ≈ 1 : BP stagne/oscille → topology boost actif377    // rawRatio → 0 : BP converge vite   → topology observe378    // EMA (α=0.30) pour éviter que boost oscille en phase avec BP379    //380    // prevIterMaxDelta = max|Δbelief| de l'itération t-1, capturé avant reset.381    const prevIterMaxDelta = maxBeliefDelta382    const rawRatio = iter > 0 && prevMaxDelta > 1e-6383      ? Math.min(1, prevIterMaxDelta / prevMaxDelta)384      : 1.0385    smoothedRatio = (1 - BP_EMA_ALPHA) * smoothedRatio + BP_EMA_ALPHA * rawRatio386    prevMaxDelta  = prevIterMaxDelta387388    const dynamicAffinityScale = (cfg.topologyBoost && cfg.topologyBoost > 0)389      ? (cfg.affinityScale ?? 0) * (1 + Math.min(390          smoothedRatio * cfg.topologyBoost,391          cfg.maxBoostCap ?? 0.5,392        ))393      : (cfg.affinityScale ?? 0)394395    maxBeliefDelta = 0396397    // Update order398    // 'residual' scheduling: update high-residual nodes first (Elidan et al., 2006).399    // Uses per-node |Δbelief| from the PREVIOUS iteration stored in perNodeResiduals.400    // On iter=0, perNodeResiduals is empty → falls through to sequential.401    let updateOrder: typeof nodes402    if (cfg.scheduling === 'residual' && perNodeResiduals.size > 0) {403      updateOrder = [...nodes].sort((a, b) =>404        (perNodeResiduals.get(b.id) ?? 0) - (perNodeResiduals.get(a.id) ?? 0)405      )406    } else {407      updateOrder = nodes408    }409410    for (const node of updateOrder) {411      if (posEvidenceMap.has(node.id) || negEvidenceMap.has(node.id)) continue412413      const isObserved  = !observedNodeIds || observedNodeIds.has(node.id)414      const prior       = isObserved ? truePriors.get(node.id)! : 0415      const leak        = isObserved ? leaks.get(node.id)!      : 0416      const sensitivity = sensMap.get(node.id)!417      const rigidity    = rigMap.get(node.id)!418      const gateType    = node.gateType  ?? 'or'419      const gateWeight  = node.gateWeight ?? 0.5420      const incoming    = graph.getIncomingEdges(node.id)421422      if (incoming.length === 0) {423        beliefs.set(node.id, prior)424        continue425      }426427      const posEdges = incoming.filter(e => e.type !== 'weakens')428      const negEdges = incoming.filter(e => e.type === 'weakens')429430      // ── Rigidity attenuation (composite with topology) ───────────431      // If topologyResult present, core nodes (haute432      // persistence + cycle) acquièrent une rigidité structurelle433      // indépendante du rigidityWeight, ils résistent au pull affinité.434      //435      // ρ_v^struct = clamp₀₁(max(ρ_v · w_ρ, clamp₀₁(pers_v · (1 + 0.4·1_{cycle}))))436      //437      // Le facteur 1.4 pour les nœuds en cycle peut porter pers_v · 1.4 > 1 quand438      // pers_v > 0.714. C'est intentionnel : clamp₀₁ est le gardien, et le boost439      // reflète l'incompressibilité structurelle des boucles de renforcement mutuel.440      let rigidityAttenuation: number441      if (cfg.topologyResult) {442        const topoProfile = cfg.topologyResult.profiles.get(node.id)443        const topoRigidity = topoProfile444          ? clamp01(topoProfile.persistence * (topoProfile.inCycle ? 1.4 : 1.0))445          : 0446        // Max entre rigidité manuelle (gated by weight) et rigidité topologique447        const structuralRigidity = clamp01(Math.max(rigidity * cfg.rigidityWeight, topoRigidity))448        rigidityAttenuation = 1 - structuralRigidity449      } else {450        // Standard path: no topology feedback451        rigidityAttenuation = 1 - rigidity * cfg.rigidityWeight452      }453454      // ── Synergy ───────────────────────────────────────────────────455      let activeParentCount = 0456      for (const edge of posEdges) {457        if ((prev.get(edge.source) ?? 0) > SYNERGY_THRESHOLD) activeParentCount++458      }459      const synergyExponent = activeParentCount >= 2460        ? 1 + SYNERGY_BOOST * Math.min(activeParentCount - 1, 3)461        : 1.0462463      // ── OR gate: Noisy-OR with synergy ────────────────────────────464      let posProduct = 1.0465      for (const edge of posEdges) {466        const srcBelief = prev.get(edge.source) ?? 0467468        // Conductivity scaling when enablePressure=true469        let conductivityScale = 1.0470        if (cfg.enablePressure && cfg.rigidityStates) {471          const srcRig = cfg.rigidityStates.get(edge.source)472          const tgtRig = cfg.rigidityStates.get(node.id)473          if (srcRig && tgtRig) {474            conductivityScale = computeEdgeConductivity(edge, srcRig, tgtRig)475          }476        }477478        const typeScale = TYPE_SCALE_POS[edge.type] ?? 0.50479        const q  = typeScale * rigidityAttenuation * conductivityScale480        const qi = clamp01(q * edge.weight * srcBelief)481        posProduct *= (1 - qi)482      }483      const posProductSyn = posEdges.length > 0 ? Math.pow(posProduct, synergyExponent) : 1.0484      const beliefOr = clamp01(1 - (1 - leak) * posProductSyn)485486      // ── AND gate (EIDOLON-AND: geometric mean of activations) ────────487      let beliefAnd = leak488      if (posEdges.length > 0) {489        let logSum = 0490        for (const edge of posEdges) {491          const srcBelief = prev.get(edge.source) ?? 0492          let conductivityScaleAnd = 1.0493          if (cfg.enablePressure && cfg.rigidityStates) {494            const srcRig = cfg.rigidityStates.get(edge.source)495            const tgtRig = cfg.rigidityStates.get(node.id)496            if (srcRig && tgtRig) {497              conductivityScaleAnd = computeEdgeConductivity(edge, srcRig, tgtRig)498            }499          }500          const q = (TYPE_SCALE_POS[edge.type] ?? 0.50) * rigidityAttenuation * conductivityScaleAnd501          const activation = q * edge.weight * srcBelief502          logSum += Math.log(Math.max(EPSILON, activation))503        }504        const andMean = Math.exp(logSum / posEdges.length)505        beliefAnd = clamp01(leak + (1 - leak) * andMean)506      }507508      // ── Combine gates ─────────────────────────────────────────────509      const effectiveGate = cfg.gateMode === 'noisyAND' ? 'and'510        : cfg.gateMode === 'noisyOR' ? 'or'511        : gateType512      let activated: number513      if (effectiveGate === 'and') {514        activated = beliefAnd515      } else if (effectiveGate === 'mixed') {516        activated = clamp01(gateWeight * beliefOr + (1 - gateWeight) * beliefAnd)517      } else {518        activated = beliefOr519      }520521      // ── Inhibition ────────────────────────────────────────────────522      let negProduct = 1.0523      for (const edge of negEdges) {524        const srcBelief = prev.get(edge.source) ?? 0525        const inh = clamp01(SCALE_NEG_WEAKENS * edge.weight * srcBelief)526        negProduct *= (1 - inh)527      }528529      let rawBelief = clamp01(activated * negProduct)530531      // ── Semantic channel (Hybrid BP/TDA) ─────────────────────────532      if (cfg.affinityMatrix && dynamicAffinityScale > 0) {533        const affinRow = cfg.affinityMatrix.get(node.id)534        const minW = cfg.affinityMinWeight ?? 0.20535        if (affinRow && affinRow.size > 0) {536          let contextSum = 0, totalAffinity = 0537          for (const [neighborId, w] of affinRow) {538            if (w < minW) continue539            const nb = prev.get(neighborId)   // Jacobi : snapshot début d'itération, cohérent avec KB edges540            if (nb === undefined) continue541            contextSum += w * nb; totalAffinity += w542          }543          if (totalAffinity > 0) {544            const contextBelief = contextSum / totalAffinity545            const α = clamp01(dynamicAffinityScale * rigidityAttenuation)546            rawBelief = clamp01((1 - α) * rawBelief + α * contextBelief)547          }548        }549      }550551      // ── Prior-anchored shrinkage (λ = sensitivity) ───────────────552      // computed = (1−λ)·prior + λ·rawBelief : shrinks toward prior.553      // λ=0 → belief fixed at prior (immune); λ=1 → fully responsive.554      const computed = clamp01(prior + sensitivity * (rawBelief - prior))555556      // ── Damping ───────────────────────────────────────────────────557      const prevBelief = prev.get(node.id) ?? 0558      const newBelief  = clamp01(cfg.damping * computed + (1 - cfg.damping) * prevBelief)559      beliefs.set(node.id, newBelief)560    }561562    // ── Re-clamp evidence ─────────────────────────────────────────563    for (const [nodeId, conf] of posEvidenceMap) beliefs.set(nodeId, conf)564    for (const [nodeId, conf] of negEvidenceMap) {565      const prior = truePriors.get(nodeId) ?? DEFAULT_PRIOR566      beliefs.set(nodeId, clamp01(prior * (1 - conf)))567    }568569    // ── Convergence check + per-node residual tracking ────────────570    for (const [id, val] of beliefs) {571      const delta = Math.abs(val - (prev.get(id) ?? 0))572      if (delta > maxBeliefDelta) maxBeliefDelta = delta573      if (cfg.scheduling === 'residual') perNodeResiduals.set(id, delta)574    }575576    cfg.onIterationComplete?.(iter, new Map(beliefs), maxBeliefDelta)577578    if (maxBeliefDelta < cfg.tolerance) {579      converged = true580      break581    }