fix: ISMCTS包庄决策——600次模拟估算P(win), 阈值45%

替换占位逻辑(大牌≥6张)为真正的蒙特卡洛评估:
- EstimateWinProbability(): 模拟N局完整对局, 统计我第一个出完的概率
- 阈值45%: 包庄收益翻倍, 略微倾斜于有利局势
- 日志: [ISMCTS posX] 包庄评估: P(win)=XX% → 包庄/不包

原理: 包庄不改变牌局流程(不像斗地主叫地主), 只翻倍输赢。
因此决策简化为 P(win|我的手牌) ≥ 阈值 → 包庄。

PdkFriendServer/Logic/IsmctsBot.cs

@@ -26,10 +26,86 @@ namespace PdkFriendServer.Logic
 
         public bool DecideBaoZhuang(PdkBotView view)
         {
-            // 包庄决策：用快速模拟评估——手牌质量高就包
-            // 简化：手牌中 >10 的大牌（J/Q/K/A/2）多就包
-            int bigCards = view.MyHand.Count(c => c.GameNum >= 11);
-            return bigCards >= 6; // ≥6 张大牌 → 有一定控制力
+            // ISMCTS 包庄决策：模拟 N 局，估算自己第一个出完的概率
+            // 包庄不改变牌局流程，只翻倍输赢：P(win)*2*gain - P(lose)*2*loss
+            // 阈值 45%——因为包庄成功收益翻倍，略微倾斜有利于局势占优
+            double winRate = EstimateWinProbability(view);
+            bool shouldBao = winRate >= 0.45;
+
+            Console.WriteLine($"[ISMCTS pos{view.MyPos}] 包庄评估: P(win)={winRate:P0} → {(shouldBao ? "包庄" : "不包")}");
+            return shouldBao;
+        }
+
+        /// <summary>模拟 N 局随机对局，统计我第一个出完的概率</summary>
+        private double EstimateWinProbability(PdkBotView view)
+        {
+            int myPos = view.MyPos;
+            var hand = view.MyHand;
+            int sims = Math.Min(_simulations, 600); // 包庄模拟用 600 次，比出牌少
+
+            int wins = 0;
+            for (int s = 0; s < sims; s++)
+            {
+                if (SimulateWin(hand, view))
+                    wins++;
+            }
+            return (double)wins / sims;
+        }
+
+        /// <summary>模拟一局只看胜负——不指定第一步出什么</summary>
+        private bool SimulateWin(TCardInfoPdkF[] myHand, PdkBotView view)
+        {
+            int myPos = view.MyPos;
+            int nextPos = myPos % 3 + 1;
+            int oppPos = (myPos + 1) % 3 + 1;
+
+            var hands = new List<TCardInfoPdkF>[3];
+            hands[myPos - 1] = new List<TCardInfoPdkF>(myHand);
+            hands[nextPos - 1] = new List<TCardInfoPdkF>();
+            hands[oppPos - 1] = new List<TCardInfoPdkF>();
+
+            var allCards = GenerateDeck();
+            var unknown = allCards.Where(c => !myHand.Any(h => h.ID == c.ID)).ToList();
+            Shuffle(unknown);
+
+            int nextCnt = view.ShenYuCard[nextPos - 1];
+            int oppCnt = view.ShenYuCard[oppPos - 1];
+            hands[nextPos - 1].AddRange(unknown.Take(nextCnt));
+            hands[oppPos - 1].AddRange(unknown.Skip(nextCnt).Take(oppCnt));
+
+            // 模拟到有人出完
+            int current = myPos;
+            var maxPlay = new PlayOutCardPdkF(); // GameNum=0 → 新一轮
+            int maxPlayer = 0;
+
+            for (int move = 0; move < 400; move++)
+            {
+                var curHand = hands[current - 1];
+                if (curHand.Count == 0) return current == myPos;
+
+                bool isNewRound = maxPlayer == current || maxPlay.GameNum == 0;
+                var curMax = isNewRound ? new PlayOutCardPdkF() : maxPlay;
+                var tips = PdkCardAlgorithm.GetTipCard(curMax, curHand.ToArray(), null, false);
+
+                if (tips != null && tips.Count > 0)
+                {
+                    var pick = tips[0];
+                    maxPlay = new PlayOutCardPdkF
+                    {
+                        Pos = (byte)current,
+                        GameNum = pick[0].GameNum,
+                        Type = pick.Count == 1 ? CardType1.DanZhang : CardType1.DuiZi,
+                        Ids = pick.Select(c => c.ID).ToArray()
+                    };
+                    maxPlayer = current;
+                    foreach (var id in maxPlay.Ids)
+                        curHand.RemoveAll(c => c.ID == id);
+                }
+                current = current % 3 + 1;
+            }
+
+            return hands[myPos - 1].Count <= hands[nextPos - 1].Count
+                && hands[myPos - 1].Count <= hands[oppPos - 1].Count;
         }
 
         public PlayOutCardPdkF DecidePlay(PdkBotView view)