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Revert to old time management (#1351)
As many users reported some problems with new time management, and recent tests on longer time controls http://tests.stockfishchess.org/tests/view/5a460e160ebc590ccbb8c35d http://tests.stockfishchess.org/tests/view/5a462f4d0ebc590ccbb8c37a are even little in favor of old time management, this revert seems as a logical step. STC: LLR: 2.95 (-2.94,2.94) [-3.00,1.00] Total: 14060 W: 2562 L: 2430 D: 9068 LTC: LLR: 3.44 (-2.94,2.94) [-3.00,1.00] Total: 31611 W: 3958 L: 3827 D: 23826 bench: 5365777 (same as master)
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3 changed files with 62 additions and 43 deletions
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@ -1497,7 +1497,7 @@ moves_loop: // When in check search starts from here
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if (Threads.ponder)
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return;
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if ( (Limits.use_time_management() && elapsed > Time.maximum())
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if ( (Limits.use_time_management() && elapsed > Time.maximum() - 10)
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|| (Limits.movetime && elapsed >= Limits.movetime)
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|| (Limits.nodes && Threads.nodes_searched() >= (uint64_t)Limits.nodes))
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Threads.stop = true;
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@ -19,6 +19,8 @@
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*/
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#include <algorithm>
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#include <cfloat>
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#include <cmath>
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#include "search.h"
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#include "timeman.h"
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@ -30,46 +32,41 @@ namespace {
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enum TimeType { OptimumTime, MaxTime };
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int remaining(int myTime, int myInc, int moveOverhead, int movesToGo,
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int moveNum, bool ponder, TimeType type) {
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const int MoveHorizon = 50; // Plan time management at most this many moves ahead
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const double MaxRatio = 7.09; // When in trouble, we can step over reserved time with this ratio
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const double StealRatio = 0.35; // However we must not steal time from remaining moves over this ratio
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if (myTime <= 0)
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return 0;
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double ratio; // Which ratio of myTime we are going to use
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// move_importance() is a skew-logistic function based on naive statistical
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// analysis of "how many games are still undecided after n half-moves". Game
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// is considered "undecided" as long as neither side has >275cp advantage.
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// Data was extracted from the CCRL game database with some simple filtering criteria.
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// Usage of increment follows quadratic distribution with the maximum at move 25
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double inc = myInc * std::max(55.0, 120 - 0.12 * (moveNum - 25) * (moveNum - 25));
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double move_importance(int ply) {
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// In moves-to-go we distribute time according to a quadratic function with
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// the maximum around move 20 for 40 moves in y time case.
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if (movesToGo)
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{
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ratio = (type == OptimumTime ? 1.0 : 6.0) / std::min(50, movesToGo);
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const double XScale = 7.64;
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const double XShift = 58.4;
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const double Skew = 0.183;
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if (moveNum <= 40)
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ratio *= 1.1 - 0.001 * (moveNum - 20) * (moveNum - 20);
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else
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ratio *= 1.5;
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return pow((1 + exp((ply - XShift) / XScale)), -Skew) + DBL_MIN; // Ensure non-zero
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}
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if (movesToGo > 1)
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ratio = std::min(0.75, ratio);
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template<TimeType T>
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int remaining(int myTime, int movesToGo, int ply, int slowMover) {
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ratio *= 1 + inc / (myTime * 8.5);
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}
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// Otherwise we increase usage of remaining time as the game goes on
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else
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{
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double k = 1 + 20 * moveNum / (500.0 + moveNum);
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ratio = (type == OptimumTime ? 0.017 : 0.07) * (k + inc / myTime);
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}
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const double TMaxRatio = (T == OptimumTime ? 1 : MaxRatio);
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const double TStealRatio = (T == OptimumTime ? 0 : StealRatio);
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int time = int(std::min(1.0, ratio) * std::max(0, myTime - moveOverhead));
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double moveImportance = (move_importance(ply) * slowMover) / 100;
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double otherMovesImportance = 0;
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if (type == OptimumTime && ponder)
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time = 5 * time / 4;
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for (int i = 1; i < movesToGo; ++i)
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otherMovesImportance += move_importance(ply + 2 * i);
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return time;
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double ratio1 = (TMaxRatio * moveImportance) / (TMaxRatio * moveImportance + otherMovesImportance);
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double ratio2 = (moveImportance + TStealRatio * otherMovesImportance) / (moveImportance + otherMovesImportance);
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return int(myTime * std::min(ratio1, ratio2)); // Intel C++ asks for an explicit cast
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}
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} // namespace
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@ -84,11 +81,12 @@ namespace {
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/// inc > 0 && movestogo == 0 means: x basetime + z increment
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/// inc > 0 && movestogo != 0 means: x moves in y minutes + z increment
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void TimeManagement::init(Search::LimitsType& limits, Color us, int ply)
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{
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int moveOverhead = Options["Move Overhead"];
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int npmsec = Options["nodestime"];
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bool ponder = Options["Ponder"];
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void TimeManagement::init(Search::LimitsType& limits, Color us, int ply) {
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int minThinkingTime = Options["Minimum Thinking Time"];
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int moveOverhead = Options["Move Overhead"];
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int slowMover = Options["Slow Mover"];
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int npmsec = Options["nodestime"];
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// If we have to play in 'nodes as time' mode, then convert from time
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// to nodes, and use resulting values in time management formulas.
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@ -105,11 +103,30 @@ void TimeManagement::init(Search::LimitsType& limits, Color us, int ply)
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limits.npmsec = npmsec;
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}
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int moveNum = (ply + 1) / 2;
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startTime = limits.startTime;
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optimumTime = remaining(limits.time[us], limits.inc[us], moveOverhead,
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limits.movestogo, moveNum, ponder, OptimumTime);
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maximumTime = remaining(limits.time[us], limits.inc[us], moveOverhead,
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limits.movestogo, moveNum, ponder, MaxTime);
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optimumTime = maximumTime = std::max(limits.time[us], minThinkingTime);
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const int MaxMTG = limits.movestogo ? std::min(limits.movestogo, MoveHorizon) : MoveHorizon;
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// We calculate optimum time usage for different hypothetical "moves to go"-values
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// and choose the minimum of calculated search time values. Usually the greatest
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// hypMTG gives the minimum values.
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for (int hypMTG = 1; hypMTG <= MaxMTG; ++hypMTG)
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{
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// Calculate thinking time for hypothetical "moves to go"-value
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int hypMyTime = limits.time[us]
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+ limits.inc[us] * (hypMTG - 1)
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- moveOverhead * (2 + std::min(hypMTG, 40));
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hypMyTime = std::max(hypMyTime, 0);
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int t1 = minThinkingTime + remaining<OptimumTime>(hypMyTime, hypMTG, ply, slowMover);
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int t2 = minThinkingTime + remaining<MaxTime >(hypMyTime, hypMTG, ply, slowMover);
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optimumTime = std::min(t1, optimumTime);
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maximumTime = std::min(t2, maximumTime);
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}
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if (Options["Ponder"])
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optimumTime += optimumTime / 4;
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}
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@ -66,7 +66,9 @@ void init(OptionsMap& o) {
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o["Ponder"] << Option(false);
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o["MultiPV"] << Option(1, 1, 500);
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o["Skill Level"] << Option(20, 0, 20);
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o["Move Overhead"] << Option(100, 0, 5000);
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o["Move Overhead"] << Option(30, 0, 5000);
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o["Minimum Thinking Time"] << Option(20, 0, 5000);
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o["Slow Mover"] << Option(89, 10, 1000);
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o["nodestime"] << Option(0, 0, 10000);
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o["UCI_Chess960"] << Option(false);
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o["SyzygyPath"] << Option("<empty>", on_tb_path);
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