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/*
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  Stockfish, a UCI chess playing engine derived from Glaurung 2.1
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  Copyright (C) 2004-2008 Tord Romstad (Glaurung author)
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  Copyright (C) 2008-2015 Marco Costalba, Joona Kiiski, Tord Romstad
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  Copyright (C) 2015-2019 Marco Costalba, Joona Kiiski, Gary Linscott, Tord Romstad
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  Stockfish is free software: you can redistribute it and/or modify
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  it under the terms of the GNU General Public License as published by
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  the Free Software Foundation, either version 3 of the License, or
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  (at your option) any later version.
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  Stockfish is distributed in the hope that it will be useful,
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  but WITHOUT ANY WARRANTY; without even the implied warranty of
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  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
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  GNU General Public License for more details.
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  You should have received a copy of the GNU General Public License
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  along with this program.  If not, see <http://www.gnu.org/licenses/>.
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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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#include "uci.h"
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TimeManagement Time; // Our global time management object
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namespace {
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  enum TimeType { OptimumTime, MaxTime };
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  constexpr int MoveHorizon   = 50;   // Plan time management at most this many moves ahead
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  constexpr double MaxRatio   = 7.3;  // When in trouble, we can step over reserved time with this ratio
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  constexpr double StealRatio = 0.34; // However we must not steal time from remaining moves over this ratio
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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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  double move_importance(int ply) {
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    constexpr double XScale = 6.85;
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    constexpr double XShift = 64.5;
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    constexpr double Skew   = 0.171;
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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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  template<TimeType T>
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  TimePoint remaining(TimePoint myTime, int movesToGo, int ply, TimePoint slowMover) {
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    constexpr double TMaxRatio   = (T == OptimumTime ? 1.0 : MaxRatio);
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    constexpr double TStealRatio = (T == OptimumTime ? 0.0 : StealRatio);
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    double moveImportance = (move_importance(ply) * slowMover) / 100.0;
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    double otherMovesImportance = 0.0;
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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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    double ratio1 = (TMaxRatio * moveImportance) / (TMaxRatio * moveImportance + otherMovesImportance);
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    double ratio2 = (moveImportance + TStealRatio * otherMovesImportance) / (moveImportance + otherMovesImportance);
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    return TimePoint(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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/// init() is called at the beginning of the search and calculates the allowed
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/// thinking time out of the time control and current game ply. We support four
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/// different kinds of time controls, passed in 'limits':
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///
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///  inc == 0 && movestogo == 0 means: x basetime  [sudden death!]
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///  inc == 0 && movestogo != 0 means: x moves in y minutes
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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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  TimePoint minThinkingTime = Options["Minimum Thinking Time"];
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  TimePoint moveOverhead    = Options["Move Overhead"];
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  TimePoint slowMover       = Options["Slow Mover"];
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  TimePoint npmsec          = Options["nodestime"];
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  TimePoint hypMyTime;
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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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  // WARNING: to avoid time losses, the given npmsec (nodes per millisecond)
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  // must be much lower than the real engine speed.
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  if (npmsec)
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  {
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      if (!availableNodes) // Only once at game start
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          availableNodes = npmsec * limits.time[us]; // Time is in msec
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      // Convert from milliseconds to nodes
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      limits.time[us] = TimePoint(availableNodes);
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      limits.inc[us] *= npmsec;
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      limits.npmsec = npmsec;
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  }
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  startTime = limits.startTime;
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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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      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, TimePoint(0));
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      TimePoint t1 = minThinkingTime + remaining<OptimumTime>(hypMyTime, hypMTG, ply, slowMover);
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      TimePoint 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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}