X-Git-Url: https://git.sesse.net/?p=stockfish;a=blobdiff_plain;f=src%2Ftimeman.cpp;h=55d98c1fa98b693a0b948d2d1175e8017d466e6c;hp=9fedd1ce4d2b1efc9a6a70e117f5d98270c3ff5d;hb=01d97521fd675ed157ff7d61e6057916abbcc56c;hpb=c150f07291aa3205d630351e21f5b6826b6c9f12 diff --git a/src/timeman.cpp b/src/timeman.cpp index 9fedd1ce..55d98c1f 100644 --- a/src/timeman.cpp +++ b/src/timeman.cpp @@ -1,7 +1,8 @@ /* Stockfish, a UCI chess playing engine derived from Glaurung 2.1 Copyright (C) 2004-2008 Tord Romstad (Glaurung author) - Copyright (C) 2008-2014 Marco Costalba, Joona Kiiski, Tord Romstad + Copyright (C) 2008-2015 Marco Costalba, Joona Kiiski, Tord Romstad + Copyright (C) 2015-2017 Marco Costalba, Joona Kiiski, Gary Linscott, Tord Romstad Stockfish is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by @@ -25,45 +26,46 @@ #include "timeman.h" #include "uci.h" +TimeManagement Time; // Our global time management object + namespace { enum TimeType { OptimumTime, MaxTime }; - const int MoveHorizon = 50; // Plan time management at most this many moves ahead - const double MaxRatio = 7.0; // When in trouble, we can step over reserved time with this ratio - const double StealRatio = 0.33; // However we must not steal time from remaining moves over this ratio - - - // move_importance() is a skew-logistic function based on naive statistical - // analysis of "how many games are still undecided after n half-moves". Game - // is considered "undecided" as long as neither side has >275cp advantage. - // Data was extracted from CCRL game database with some simple filtering criteria. + int remaining(int myTime, int myInc, int moveOverhead, + int movesToGo, int ply, TimeType type) { - double move_importance(int ply) { + if (myTime <= 0) + return 0; - const double XScale = 9.3; - const double XShift = 59.8; - const double Skew = 0.172; + int moveNumber = (ply + 1) / 2; + double ratio; // Which ratio of myTime we are going to use. It is <= 1 + double sd = 8.5; - return pow((1 + exp((ply - XShift) / XScale)), -Skew) + DBL_MIN; // Ensure non-zero - } - - template - int remaining(int myTime, int movesToGo, int ply, int slowMover) - { - const double TMaxRatio = (T == OptimumTime ? 1 : MaxRatio); - const double TStealRatio = (T == OptimumTime ? 0 : StealRatio); + // Usage of increment follows quadratic distribution with the maximum at move 25 + double inc = myInc * std::max(55.0, 120.0 - 0.12 * (moveNumber - 25) * (moveNumber - 25)); - double moveImportance = (move_importance(ply) * slowMover) / 100; - double otherMovesImportance = 0; + // In moves-to-go we distribute time according to a quadratic function with + // the maximum around move 20 for 40 moves in y time case. + if (movesToGo) + { + ratio = (type == OptimumTime ? 1.0 : 6.0) / std::min(50, movesToGo); - for (int i = 1; i < movesToGo; ++i) - otherMovesImportance += move_importance(ply + 2 * i); + if (moveNumber <= 40) + ratio *= 1.1 - 0.001 * (moveNumber - 20) * (moveNumber - 20); + else + ratio *= 1.5; + } + // Otherwise we increase usage of remaining time as the game goes on + else + { + sd = 1 + 20 * moveNumber / (500.0 + moveNumber); + ratio = (type == OptimumTime ? 0.017 : 0.07) * sd; + } - double ratio1 = (TMaxRatio * moveImportance) / (TMaxRatio * moveImportance + otherMovesImportance); - double ratio2 = (moveImportance + TStealRatio * otherMovesImportance) / (moveImportance + otherMovesImportance); + ratio = std::min(1.0, ratio * (1 + inc / (myTime * sd))); - return int(myTime * std::min(ratio1, ratio2)); // Intel C++ asks an explicit cast + return int(ratio * std::max(0, myTime - moveOverhead)); } } // namespace @@ -78,39 +80,30 @@ namespace { /// inc > 0 && movestogo == 0 means: x basetime + z increment /// inc > 0 && movestogo != 0 means: x moves in y minutes + z increment -void TimeManager::init(const Search::LimitsType& limits, Color us, int ply) +void TimeManagement::init(Search::LimitsType& limits, Color us, int ply) { - int minThinkingTime = Options["Minimum Thinking Time"]; int moveOverhead = Options["Move Overhead"]; - int slowMover = Options["Slow Mover"]; + int npmsec = Options["nodestime"]; - // Initialize unstablePvFactor to 1 and search times to maximum values - unstablePvFactor = 1; - optimumSearchTime = maximumSearchTime = std::max(limits.time[us], minThinkingTime); - - const int MaxMTG = limits.movestogo ? std::min(limits.movestogo, MoveHorizon) : MoveHorizon; - - // We calculate optimum time usage for different hypothetical "moves to go"-values - // and choose the minimum of calculated search time values. Usually the greatest - // hypMTG gives the minimum values. - for (int hypMTG = 1; hypMTG <= MaxMTG; ++hypMTG) + // If we have to play in 'nodes as time' mode, then convert from time + // to nodes, and use resulting values in time management formulas. + // WARNING: Given npms (nodes per millisecond) must be much lower then + // the real engine speed to avoid time losses. + if (npmsec) { - // Calculate thinking time for hypothetical "moves to go"-value - int hypMyTime = limits.time[us] - + limits.inc[us] * (hypMTG - 1) - - moveOverhead * (2 + std::min(hypMTG, 40)); - - hypMyTime = std::max(hypMyTime, 0); + if (!availableNodes) // Only once at game start + availableNodes = npmsec * limits.time[us]; // Time is in msec - int t1 = minThinkingTime + remaining(hypMyTime, hypMTG, ply, slowMover); - int t2 = minThinkingTime + remaining(hypMyTime, hypMTG, ply, slowMover); - - optimumSearchTime = std::min(t1, optimumSearchTime); - maximumSearchTime = std::min(t2, maximumSearchTime); + // Convert from millisecs to nodes + limits.time[us] = (int)availableNodes; + limits.inc[us] *= npmsec; + limits.npmsec = npmsec; } - if (Options["Ponder"]) - optimumSearchTime += optimumSearchTime / 4; + startTime = limits.startTime; + optimumTime = remaining(limits.time[us], limits.inc[us], moveOverhead, limits.movestogo, ply, OptimumTime); + maximumTime = remaining(limits.time[us], limits.inc[us], moveOverhead, limits.movestogo, ply, MaxTime); - optimumSearchTime = std::min(optimumSearchTime, maximumSearchTime); + if (Options["Ponder"]) + optimumTime += optimumTime / 4; }