diff --git a/MQL5/Experts/MultiAgentTest/Core/NeuralNet.mqh b/MQL5/Experts/MultiAgentTest/Core/NeuralNet.mqh
index fdd82e0..e15bc71 100644
--- a/MQL5/Experts/MultiAgentTest/Core/NeuralNet.mqh
+++ b/MQL5/Experts/MultiAgentTest/Core/NeuralNet.mqh
@@ -498,9 +498,9 @@ for(int i = 0; i < m_hidden; i++) {
          first, last, best, bestEpoch+1, ArraySize(m_lossHistory));
    }
 
-   int Predict(vector &input) {
-      vector output;
-      Forward(input, output);
+int Predict(vector &inp) {
+       vector output;
+       Forward(inp, output);
       int bestIdx = 0;
       double bestVal = output[0];
       for(int i = 1; i < m_outputs; i++) {
@@ -512,9 +512,9 @@ for(int i = 0; i < m_hidden; i++) {
       return bestIdx;
    }
 
-   double GetCombinedZ(vector &input) {
-      vector output;
-      Forward(input, output);
+double GetCombinedZ(vector &inp) {
+       vector output;
+       Forward(inp, output);
       return output[0] - output[2];
    }
 
diff --git a/MQL5/Experts/MultiAgentTest/Core/Orchestrator.mqh b/MQL5/Experts/MultiAgentTest/Core/Orchestrator.mqh
index 38585bb..6b5bc39 100644
--- a/MQL5/Experts/MultiAgentTest/Core/Orchestrator.mqh
+++ b/MQL5/Experts/MultiAgentTest/Core/Orchestrator.mqh
@@ -424,42 +424,41 @@ public:
             Print("ERROR: slot non disponibile nonostante capacity expansion");
             return -1;
          }
-TrackedTrade *t = &openTrades[idx];
-        t.ticket    = ticket;
-        t.entryPrice = price;
-        t.entryATR  = MathMax(atr, 1e-10);
-        t.entryZ    = z;
-        t.isBuy     = isBuy;
-        t.highestPrice = price;
-        t.lowestPrice  = price;
-        t.barsHeld  = 0;
-        t.maeATR    = 0;
-        t.mfeATR    = 0;
-        t.active    = true;
+openTrades[idx].ticket     = ticket;
+        openTrades[idx].entryPrice  = price;
+        openTrades[idx].entryATR    = MathMax(atr, 1e-10);
+        openTrades[idx].entryZ      = z;
+        openTrades[idx].isBuy       = isBuy;
+        openTrades[idx].highestPrice = price;
+        openTrades[idx].lowestPrice  = price;
+        openTrades[idx].barsHeld    = 0;
+        openTrades[idx].maeATR      = 0;
+        openTrades[idx].mfeATR      = 0;
+        openTrades[idx].active      = true;
 
         for(int i=0; i<agentCount; i++)
-           t.entryZScores[i] = agents[i].lastZScore;
+           openTrades[idx].entryZScores[i] = agents[i].lastZScore;
 
         // Feature vector per NN
-        for(int f = 0; f < NN_FEATURES; f++) t.entryFeatures[f] = 0.0;
+        for(int f = 0; f < NN_FEATURES; f++) openTrades[idx].entryFeatures[f] = 0.0;
         for(int i=0; i<agentCount; i++) {
-                 if(agents[i].name == "Hurst")     t.entryFeatures[0] = agents[i].lastZScore;
-            else if(agents[i].name == "ADX")       t.entryFeatures[1] = agents[i].lastZScore;
-            else if(agents[i].name == "MA")        t.entryFeatures[2] = agents[i].lastZScore;
-            else if(agents[i].name == "Momentum")  t.entryFeatures[3] = agents[i].lastZScore;
-            else if(agents[i].name == "Consensus") t.entryFeatures[4] = agents[i].lastZScore;
-            else if(agents[i].name == "Hunter")    t.entryFeatures[5] = agents[i].lastZScore;
+                 if(agents[i].name == "Hurst")     openTrades[idx].entryFeatures[0] = agents[i].lastZScore;
+            else if(agents[i].name == "ADX")       openTrades[idx].entryFeatures[1] = agents[i].lastZScore;
+            else if(agents[i].name == "MA")        openTrades[idx].entryFeatures[2] = agents[i].lastZScore;
+            else if(agents[i].name == "Momentum")  openTrades[idx].entryFeatures[3] = agents[i].lastZScore;
+            else if(agents[i].name == "Consensus") openTrades[idx].entryFeatures[4] = agents[i].lastZScore;
+            else if(agents[i].name == "Hunter")    openTrades[idx].entryFeatures[5] = agents[i].lastZScore;
         }
-        t.entryFeatures[6] = SHARED_regimeAgreement;
-        t.entryFeatures[7] = SHARED_trendStrength;
+        openTrades[idx].entryFeatures[6] = SHARED_regimeAgreement;
+        openTrades[idx].entryFeatures[7] = SHARED_trendStrength;
 
         // SL iniziale adattivo
         double slWidth = AdaptiveSLWidth();
-        t.slPrice = isBuy ? price - atr * slWidth : price + atr * slWidth;
+        openTrades[idx].slPrice = isBuy ? price - atr * slWidth : price + atr * slWidth;
 
         Print("Trade #", ticket, " ", isBuy ? "BUY" : "SELL",
               " entry=", price, " z=", StringFormat("%+.3f", z),
-              " SL=", StringFormat("%.5f", t.slPrice),
+              " SL=", StringFormat("%.5f", openTrades[idx].slPrice),
               " (", StringFormat("%.1f", slWidth), " ATR)");
         return idx;
      }
@@ -476,44 +475,42 @@ void OnTradeClose(int ticket, double closePrice) {
        }
        if(idx < 0) return;
 
-       TrackedTrade *t = &openTrades[idx];
+       // Calcola MAE/MFE finali
+       if(openTrades[idx].isBuy) {
+          openTrades[idx].maeATR = (openTrades[idx].entryPrice - openTrades[idx].lowestPrice) / openTrades[idx].entryATR;
+          openTrades[idx].mfeATR = (openTrades[idx].highestPrice - openTrades[idx].entryPrice) / openTrades[idx].entryATR;
+       } else {
+          openTrades[idx].maeATR = (openTrades[idx].highestPrice - openTrades[idx].entryPrice) / openTrades[idx].entryATR;
+          openTrades[idx].mfeATR = (openTrades[idx].entryPrice - openTrades[idx].lowestPrice) / openTrades[idx].entryATR;
+       }
 
-      // Calcola MAE/MFE finali
-      if(t.isBuy) {
-         t.maeATR = (t.entryPrice - t.lowestPrice) / t.entryATR;
-         t.mfeATR = (t.highestPrice - t.entryPrice) / t.entryATR;
-      } else {
-         t.maeATR = (t.highestPrice - t.entryPrice) / t.entryATR;
-         t.mfeATR = (t.entryPrice - t.lowestPrice) / t.entryATR;
-      }
+       // ROI in ATR (positivo = profitto nella direzione del trade)
+       double actualReturn = openTrades[idx].isBuy
+          ? (closePrice - openTrades[idx].entryPrice) / openTrades[idx].entryATR
+          : (openTrades[idx].entryPrice - closePrice) / openTrades[idx].entryATR;
 
-      // ROI in ATR (positivo = profitto nella direzione del trade)
-      double actualReturn = t.isBuy
-         ? (closePrice - t.entryPrice) / t.entryATR
-         : (t.entryPrice - closePrice) / t.entryATR;
+       returnStats.Update(actualReturn);
+       maeStats.Update(openTrades[idx].maeATR);
+       mfeStats.Update(openTrades[idx].mfeATR);
+       if(actualReturn > 0) maeWinStats.Update(openTrades[idx].maeATR);
 
-      returnStats.Update(actualReturn);
-      maeStats.Update(t.maeATR);
-      mfeStats.Update(t.mfeATR);
-      if(actualReturn > 0) maeWinStats.Update(t.maeATR);
+       tradeReturns[tradeCount % ROLLING_TRADES] = actualReturn;
+       tradeCount++;
+       if(actualReturn > 0) winCount++;
 
-      tradeReturns[tradeCount % ROLLING_TRADES] = actualReturn;
-      tradeCount++;
-      if(actualReturn > 0) winCount++;
+       double eq = AccountInfoDouble(ACCOUNT_EQUITY);
+       if(eq > peakEquity) peakEquity = eq;
+       double dd = (peakEquity > 0) ? (peakEquity - eq) / peakEquity : 0;
+       if(dd > maxDrawdown) maxDrawdown = dd;
+       double actualReturnZ = returnStats.RawZScore(actualReturn);
 
-      double eq = AccountInfoDouble(ACCOUNT_EQUITY);
-      if(eq > peakEquity) peakEquity = eq;
-      double dd = (peakEquity > 0) ? (peakEquity - eq) / peakEquity : 0;
-      if(dd > maxDrawdown) maxDrawdown = dd;
-      double actualReturnZ = returnStats.RawZScore(actualReturn);
-
-      Print("=== Learning: Trade #", ticket, " ", t.isBuy ? "BUY" : "SELL", " chiuso ===");
-      Print("  Return: ", StringFormat("%+.2f ATR", actualReturn),
-            " | MAE: ", StringFormat("%.2f", t.maeATR),
-            " | MFE: ", StringFormat("%.2f", t.mfeATR),
-            " | bars: ", t.barsHeld);
-      Print("  Entry z=", StringFormat("%+.3f", t.entryZ),
-            " | SL width: ", StringFormat("%.2f ATR", AdaptiveSLWidth()));
+       Print("=== Learning: Trade #", ticket, " ", openTrades[idx].isBuy ? "BUY" : "SELL", " chiuso ===");
+       Print("  Return: ", StringFormat("%+.2f ATR", actualReturn),
+             " | MAE: ", StringFormat("%.2f", openTrades[idx].maeATR),
+             " | MFE: ", StringFormat("%.2f", openTrades[idx].mfeATR),
+             " | bars: ", openTrades[idx].barsHeld);
+       Print("  Entry z=", StringFormat("%+.3f", openTrades[idx].entryZ),
+             " | SL width: ", StringFormat("%.2f ATR", AdaptiveSLWidth()));
 
       double sigThr = combinedZStats.Ready()
          ? combinedZStats.Std() / MathSqrt(MathMax(1, agentCount))
@@ -521,55 +518,55 @@ void OnTradeClose(int ticket, double closePrice) {
       for(int i=0; i<agentCount; i++) {
          if(MathAbs(t.entryZScores[i]) < sigThr) continue;
 
-         UpdateCorrelation(i, t.entryZScores[i], actualReturnZ);
-         double rho = GetCorrelation(i);
+UpdateCorrelation(i, openTrades[idx].entryZScores[i], actualReturnZ);
+          double rho = GetCorrelation(i);
 
-         agents[i].weight = MathMax(weightMin, rho);
+          agents[i].weight = MathMax(weightMin, rho);
 
-         agents[i].Learn(t.entryZScores[i], actualReturnZ);
+          agents[i].Learn(openTrades[idx].entryZScores[i], actualReturnZ);
 
-         double bias = agents[i].predictionError.Mean();
-         double biasStd = agents[i].predictionError.Std();
-         double rhoLearn = agents[i].predCorr.Ready() ? agents[i].predCorr.Correlation() : 0;
+          double bias = agents[i].predictionError.Mean();
+          double biasStd = agents[i].predictionError.Std();
+          double rhoLearn = agents[i].predCorr.Ready() ? agents[i].predCorr.Correlation() : 0;
 
-         Print("  ", agents[i].name,
-               " | pred=", StringFormat("%+.2f", t.entryZScores[i]),
-               " | ρ=", StringFormat("%+.3f", rho),
-               " | w=", StringFormat("%.3f", agents[i].weight),
-               " | bias=", StringFormat("%+.4f", bias),
-               " | biasσ=", StringFormat("%.4f", biasStd),
-               " | ρ_learn=", StringFormat("%+.3f", rhoLearn));
-      }
+          Print("  ", agents[i].name,
+                " | pred=", StringFormat("%+.2f", openTrades[idx].entryZScores[i]),
+                " | ρ=", StringFormat("%+.3f", rho),
+                " | w=", StringFormat("%.3f", agents[i].weight),
+                " | bias=", StringFormat("%+.4f", bias),
+                " | biasσ=", StringFormat("%.4f", biasStd),
+                " | ρ_learn=", StringFormat("%+.3f", rhoLearn));
+       }
 
-       // --- Neural Network: colleziona training sample ---
-       if(m_trainMode && m_trainBuffer != NULL && m_neuralNet != NULL) {
-          double features[NN_FEATURES];
-          double target[NN_TARGETS];
-          for(int f = 0; f < NN_FEATURES; f++) features[f] = t.entryFeatures[f];
+        // --- Neural Network: colleziona training sample ---
+        if(m_trainMode && m_trainBuffer != NULL && m_neuralNet != NULL) {
+           double features[NN_FEATURES];
+           double target[NN_TARGETS];
+           for(int f = 0; f < NN_FEATURES; f++) features[f] = openTrades[idx].entryFeatures[f];
 
-          target[0] = 0; target[1] = 0; target[2] = 0;
-          int tradeDir = t.isBuy ? 1 : -1;
+           target[0] = 0; target[1] = 0; target[2] = 0;
+           int tradeDir = openTrades[idx].isBuy ? 1 : -1;
 
-          if(actualReturn > 0) {
-             if(tradeDir == 1)     target[0] = 1;
-             else                  target[2] = 1;
-          } else {
-             if(tradeDir == 1)     target[2] = 1;
-             else                  target[0] = 1;
-          }
+           if(actualReturn > 0) {
+              if(tradeDir == 1)     target[0] = 1;
+              else                  target[2] = 1;
+           } else {
+              if(tradeDir == 1)     target[2] = 1;
+              else                  target[0] = 1;
+           }
 
-           double sampleWeight = MathAbs(actualReturn) + 1.0;  // trade profittevoli/perdenti pesano di più
-           m_trainBuffer.Add(features, target, sampleWeight);
+            double sampleWeight = MathAbs(actualReturn) + 1.0;  // trade profittevoli/perdenti pesano di più
+            m_trainBuffer.Add(features, target, sampleWeight);
 
-           if(m_trainBuffer.Count() < 20)
-              Print("  NN sample #", m_trainBuffer.Count(), " collected (w=", StringFormat("%.2f", sampleWeight), ")");
+            if(m_trainBuffer.Count() < 20)
+               Print("  NN sample #", m_trainBuffer.Count(), " collected (w=", StringFormat("%.2f", sampleWeight), ")");
 
-          if(m_trainBuffer.Count() % 50 == 0 && m_trainBuffer.Count() >= 20) {
-             if(m_useNeural) {
-                TrainNN();
-                string nnFn = (m_modelFilename != "") ? m_modelFilename : "TR_Agent_NN_v1.dat";
-                m_neuralNet.Save(nnFn);
-                Print("  NN auto-saved to ", nnFn, " after ", m_trainBuffer.Count(), " samples");
+           if(m_trainBuffer.Count() % 50 == 0 && m_trainBuffer.Count() >= 20) {
+              if(m_useNeural) {
+                 TrainNN();
+                 string nnFn = (m_modelFilename != "") ? m_modelFilename : "TR_Agent_NN_v1.dat";
+                 m_neuralNet.Save(nnFn);
+                 Print("  NN auto-saved to ", nnFn, " after ", m_trainBuffer.Count(), " samples");
              }
           }
        }
@@ -588,40 +585,38 @@ void OnTradeClose(int ticket, double closePrice) {
    }
 
 // Aggiorna MAE/MFE per tutti i trade aperti (chiamato ogni barra)
-    void UpdateOpenTrades(double high, double low) {
-       for(int i=0; i<maxOpenTrades; i++) {
-          if(!openTrades[i].active) continue;
-          TrackedTrade *t = &openTrades[i];
-          if(high > t.highestPrice) t.highestPrice = high;
-          if(low  < t.lowestPrice)  t.lowestPrice  = low;
-          t.barsHeld++;
-       }
-    }
+     void UpdateOpenTrades(double high, double low) {
+        for(int i=0; i<maxOpenTrades; i++) {
+           if(!openTrades[i].active) continue;
+           if(high > openTrades[i].highestPrice) openTrades[i].highestPrice = high;
+           if(low  < openTrades[i].lowestPrice)  openTrades[i].lowestPrice  = low;
+           openTrades[i].barsHeld++;
+        }
+     }
 
-    // Trailing stop: sposta SL dopo che il profitto supera la soglia
-    void TrailStops() {
-       for(int i=0; i<maxOpenTrades; i++) {
-          if(!openTrades[i].active) continue;
-          TrackedTrade *t = &openTrades[i];
+     // Trailing stop: sposta SL dopo che il profitto supera la soglia
+     void TrailStops() {
+        for(int i=0; i<maxOpenTrades; i++) {
+           if(!openTrades[i].active) continue;
 
-          double profitATR = t.isBuy
-             ? (t.highestPrice - t.entryPrice) / t.entryATR
-             : (t.entryPrice - t.lowestPrice) / t.entryATR;
+           double profitATR = openTrades[i].isBuy
+              ? (openTrades[i].highestPrice - openTrades[i].entryPrice) / openTrades[i].entryATR
+              : (openTrades[i].entryPrice - openTrades[i].lowestPrice) / openTrades[i].entryATR;
 
-          double trigger = AdaptiveTrailTrigger();
-          if(profitATR > trigger) {
-             double offset = AdaptiveTrailOffset();
-             double newSL;
-             if(t.isBuy) {
-                newSL = t.highestPrice - offset * t.entryATR;
-                if(newSL > t.slPrice) t.slPrice = newSL;
-             } else {
-                newSL = t.lowestPrice + offset * t.entryATR;
-                if(newSL < t.slPrice) t.slPrice = newSL;
-             }
-          }
-       }
-    }
+           double trigger = AdaptiveTrailTrigger();
+           if(profitATR > trigger) {
+              double offset = AdaptiveTrailOffset();
+              double newSL;
+              if(openTrades[i].isBuy) {
+                 newSL = openTrades[i].highestPrice - offset * openTrades[i].entryATR;
+                 if(newSL > openTrades[i].slPrice) openTrades[i].slPrice = newSL;
+              } else {
+                 newSL = openTrades[i].lowestPrice + offset * openTrades[i].entryATR;
+                 if(newSL < openTrades[i].slPrice) openTrades[i].slPrice = newSL;
+              }
+           }
+        }
+     }
 
    // Trade da chiudere per inversione di segnale (ritorna array di ticket)
    void GetTradesToClose(int &closeTickets[], double currentZ, double minZ) {