X-Git-Url: https://git.sesse.net/?a=blobdiff_plain;ds=sidebyside;f=src%2Fsearch.cpp;h=9a62fb793290e5cd49b241653645f532ed8f778c;hb=d173285da5d7683083d853ca8fba5672376f5aba;hp=9a3ecbbefaf8fecaa63b67c161731f6e5ee4b25d;hpb=920b1abede63303a991a014d8de069856e81f046;p=stockfish

diff --git a/src/search.cpp b/src/search.cpp
index 9a3ecbbe..9a62fb79 100644
--- a/src/search.cpp
+++ b/src/search.cpp
@@ -243,7 +243,7 @@ namespace {
   RootMoveList Rml;
 
   // MultiPV mode
-  int MultiPV;
+  int MultiPV, UCIMultiPV;
 
   // Time management variables
   int SearchStartTime, MaxNodes, MaxDepth, ExactMaxTime;
@@ -255,6 +255,10 @@ namespace {
   bool UseLogFile;
   std::ofstream LogFile;
 
+  // Skill level adjustment
+  int SkillLevel;
+  RKISS RK;
+
   // Multi-threads manager object
   ThreadsManager ThreadsMgr;
 
@@ -503,11 +507,16 @@ bool think(Position& pos, bool infinite, bool ponder, int time[], int increment[
   PawnEndgameExtension[0]   = Options["Pawn Endgame Extension (non-PV nodes)"].value<Depth>();
   MateThreatExtension[1]    = Options["Mate Threat Extension (PV nodes)"].value<Depth>();
   MateThreatExtension[0]    = Options["Mate Threat Extension (non-PV nodes)"].value<Depth>();
-  MultiPV                   = Options["MultiPV"].value<int>();
+  UCIMultiPV                = Options["MultiPV"].value<int>();
+  SkillLevel                = Options["Skill level"].value<int>();
   UseLogFile                = Options["Use Search Log"].value<bool>();
 
   read_evaluation_uci_options(pos.side_to_move());
 
+  // Do we have to play with skill handicap? In this case enable MultiPV that
+  // we will use behind the scenes to retrieve a set of possible moves.
+  MultiPV = (SkillLevel < 20 ? Max(UCIMultiPV, 4) : UCIMultiPV);
+
   // Set the number of active threads
   ThreadsMgr.read_uci_options();
   init_eval(ThreadsMgr.active_threads());
@@ -633,7 +642,7 @@ namespace {
     while (++depth <= PLY_MAX && (!MaxDepth || depth <= MaxDepth) && !StopRequest)
     {
         Rml.bestMoveChanges = 0;
-        cout << "info depth " << depth << endl;
+        cout << set960(pos.is_chess960()) << "info depth " << depth << endl;
 
         // Calculate dynamic aspiration window based on previous iterations
         if (MultiPV == 1 && depth >= 5 && abs(bestValues[depth - 1]) < VALUE_KNOWN_WIN)
@@ -654,14 +663,10 @@ namespace {
             // Search starting from ss+1 to allow calling update_gains()
             value = search<PV, false, true>(pos, ss+1, alpha, beta, depth * ONE_PLY, 0);
 
-            // Send PV line to GUI and write to transposition table in case the
-            // relevant entries have been overwritten during the search.
+            // Write PV back to transposition table in case the relevant entries
+            // have been overwritten during the search.
             for (int i = 0; i < Min(MultiPV, (int)Rml.size()); i++)
-            {
                 Rml[i].insert_pv_in_tt(pos);
-                cout << set960(pos.is_chess960())
-                     << Rml[i].pv_info_to_uci(pos, depth, alpha, beta, i) << endl;
-            }
 
             // Value cannot be trusted. Break out immediately!
             if (StopRequest)
@@ -691,9 +696,14 @@ namespace {
 
         // Collect info about search result
         bestMove = Rml[0].pv[0];
+        *ponderMove = Rml[0].pv[1];
         bestValues[depth] = value;
         bestMoveChanges[depth] = Rml.bestMoveChanges;
 
+        // Send PV line to GUI and to log file
+        for (int i = 0; i < Min(UCIMultiPV, (int)Rml.size()); i++)
+            cout << Rml[i].pv_info_to_uci(pos, depth, alpha, beta, i) << endl;
+
         if (UseLogFile)
             LogFile << pretty_pv(pos, depth, value, current_search_time(), Rml[0].pv) << endl;
 
@@ -746,7 +756,47 @@ namespace {
         }
     }
 
-    *ponderMove = Rml[0].pv[1];
+    // When playing with strength handicap choose best move among the MultiPV set
+    // using a statistical rule dependent on SkillLevel. Idea by Heinz van Saanen.
+    if (SkillLevel < 20)
+    {
+        assert(MultiPV > 1);
+
+        // Rml list is already sorted by pv_score in descending order
+        int s;
+        int max_s = -VALUE_INFINITE;
+        int size = Min(MultiPV, (int)Rml.size());
+        int max = Rml[0].pv_score;
+        int var = Min(max - Rml[size - 1].pv_score, PawnValueMidgame);
+        int wk = 120 - 2 * SkillLevel;
+
+        // PRNG sequence should be non deterministic
+        for (int i = abs(get_system_time() % 50); i > 0; i--)
+            RK.rand<unsigned>();
+
+        // Choose best move. For each move's score we add two terms both dependent
+        // on wk, one deterministic and bigger for weaker moves, and one random,
+        // then we choose the move with the resulting highest score.
+        for (int i = 0; i < size; i++)
+        {
+            s = Rml[i].pv_score;
+
+            // Don't allow crazy blunders even at very low skills
+            if (i > 0 && Rml[i-1].pv_score > s + EasyMoveMargin)
+                break;
+
+            // This is our magical formula
+            s += ((max - s) * wk + var * (RK.rand<unsigned>() % wk)) / 128;
+
+            if (s > max_s)
+            {
+                max_s = s;
+                bestMove = Rml[i].pv[0];
+                *ponderMove = Rml[i].pv[1];
+            }
+        }
+    }
+
     return bestMove;
   }
 
@@ -1056,7 +1106,7 @@ split_point_start: // At split points actual search starts from here
 
           if (abs(ttValue) < VALUE_KNOWN_WIN)
           {
-              Value b = ttValue - depth;
+              Value b = ttValue - int(depth);
               ss->excludedMove = move;
               ss->skipNullMove = true;
               Value v = search<NonPV>(pos, ss, b - 1, b, depth / 2, ply);