X-Git-Url: https://git.sesse.net/?p=stockfish;a=blobdiff_plain;f=src%2Fsearch.cpp;h=2c2321ee9ca0bb5f48bd99b4fc068986a8d2a297;hp=e6446768066afa33f95d8b6f2aec9faa62abc90e;hb=0dbc72d82e7f5f314499b22a04dcef45edcdba9a;hpb=4ae5a7b45a430aea5f4b21f9455b4db74ed1c44a

diff --git a/src/search.cpp b/src/search.cpp
index e6446768..2c2321ee 100644
--- a/src/search.cpp
+++ b/src/search.cpp
@@ -271,7 +271,7 @@ void MainThread::search() {
   // Check if there are threads with a better score than main thread
   if (    Options["MultiPV"] == 1
       && !Limits.depth
-      && !Skill(Options["Skill Level"]).enabled()
+      && !(Skill(Options["Skill Level"]).enabled() || Options["UCI_LimitStrength"])
       &&  rootMoves[0].pv[0] != MOVE_NONE)
   {
       std::map<Move, int64_t> votes;
@@ -335,11 +335,18 @@ void Thread::search() {
   beta = VALUE_INFINITE;
 
   multiPV = Options["MultiPV"];
+
   // Pick integer skill levels, but non-deterministically round up or down
   // such that the average integer skill corresponds to the input floating point one.
+  // UCI_Elo is converted to a suitable fractional skill level, using anchoring
+  // to CCRL Elo (goldfish 1.13 = 2000) and a fit through Ordo derived Elo
+  // for match (TC 60+0.6) results spanning a wide range of k values.
   PRNG rng(now());
-  int intLevel = int(Options["Skill Level"]) +
-        ((Options["Skill Level"] - int(Options["Skill Level"])) * 1024 > rng.rand<unsigned>() % 1024  ? 1 : 0);
+  double floatLevel = Options["UCI_LimitStrength"] ?
+                        clamp(std::pow((Options["UCI_Elo"] - 1346.6) / 143.4, 1 / 0.806), 0.0, 20.0) :
+                        double(Options["Skill Level"]);
+  int intLevel = int(floatLevel) +
+                 ((floatLevel - int(floatLevel)) * 1024 > rng.rand<unsigned>() % 1024  ? 1 : 0);
   Skill skill(intLevel);
 
   // When playing with strength handicap enable MultiPV search that we will
@@ -503,7 +510,7 @@ void Thread::search() {
 
           // If the bestMove is stable over several iterations, reduce time accordingly
           timeReduction = lastBestMoveDepth + 10 * ONE_PLY < completedDepth ? 1.95 : 1.0;
-          double reduction = std::pow(mainThread->previousTimeReduction, 0.528) / timeReduction;
+          double reduction = (1.25 + mainThread->previousTimeReduction) / (2.25 * timeReduction);
 
           // Use part of the gained time from a previous stable move for the current move
           for (Thread* th : Threads)
@@ -578,7 +585,7 @@ namespace {
     Move ttMove, move, excludedMove, bestMove;
     Depth extension, newDepth;
     Value bestValue, value, ttValue, eval, maxValue;
-    bool ttHit, ttPv, inCheck, givesCheck, improving;
+    bool ttHit, ttPv, inCheck, givesCheck, improving, doLMR;
     bool captureOrPromotion, doFullDepthSearch, moveCountPruning, ttCapture;
     Piece movedPiece;
     int moveCount, captureCount, quietCount, singularLMR;
@@ -1122,15 +1129,25 @@ moves_loop: // When in check, search starts from here
 
           value = -search<NonPV>(pos, ss+1, -(alpha+1), -alpha, d, true);
 
-          doFullDepthSearch = (value > alpha && d != newDepth);
+          doFullDepthSearch = (value > alpha && d != newDepth), doLMR = true;
       }
       else
-          doFullDepthSearch = !PvNode || moveCount > 1;
+          doFullDepthSearch = !PvNode || moveCount > 1, doLMR = false;
 
       // Step 17. Full depth search when LMR is skipped or fails high
       if (doFullDepthSearch)
+      {
           value = -search<NonPV>(pos, ss+1, -(alpha+1), -alpha, newDepth, !cutNode);
 
+          if (doLMR && !captureOrPromotion)
+          {
+              int bonus = value > alpha ?  stat_bonus(newDepth)
+                                        : -stat_bonus(newDepth);
+
+              update_continuation_histories(ss, movedPiece, to_sq(move), bonus);
+          }
+      }
+
       // For PV nodes only, do a full PV search on the first move or after a fail
       // high (in the latter case search only if value < beta), otherwise let the
       // parent node fail low with value <= alpha and try another move.