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DroidFish: Updated stockfish engine to development version 2017-09-06.

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Peter Osterlund
2017-09-10 10:30:09 +02:00
parent c0b69b6bf8
commit 3536c6290a
42 changed files with 3431 additions and 4042 deletions
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100
DroidFish/jni/stockfish/timeman.cpp
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@@ -2,7 +2,7 @@
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2008 Tord Romstad (Glaurung author)
Copyright (C) 2008-2015 Marco Costalba, Joona Kiiski, Tord Romstad
Copyright (C) 2015-2016 Marco Costalba, Joona Kiiski, Gary Linscott, 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
@@ -19,8 +19,6 @@
*/
#include <algorithm>
#include <cfloat>
#include <cmath>
#include "search.h"
#include "timeman.h"
@@ -32,41 +30,43 @@ namespace {
enum TimeType { OptimumTime, MaxTime };
const int MoveHorizon = 50; // Plan time management at most this many moves ahead
const double MaxRatio = 7.09; // When in trouble, we can step over reserved time with this ratio
const double StealRatio = 0.35; // However we must not steal time from remaining moves over this ratio
int remaining(int myTime, int myInc, int moveOverhead, int movesToGo,
int moveNum, bool ponder, TimeType type) {
if (myTime <= 0)
return 0;
// 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 the CCRL game database with some simple filtering criteria.
double ratio; // Which ratio of myTime we are going to use
double move_importance(int ply) {
// Usage of increment follows quadratic distribution with the maximum at move 25
double inc = myInc * std::max(55.0, 120 - 0.12 * (moveNum - 25) * (moveNum - 25));
const double XScale = 7.64;
const double XShift = 58.4;
const double Skew = 0.183;
// 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);
return pow((1 + exp((ply - XShift) / XScale)), -Skew) + DBL_MIN; // Ensure non-zero
}
if (moveNum <= 40)
ratio *= 1.1 - 0.001 * (moveNum - 20) * (moveNum - 20);
else
ratio *= 1.5;
template<TimeType T>
int remaining(int myTime, int movesToGo, int ply, int slowMover) {
ratio *= 1 + inc / (myTime * 8.5);
}
// Otherwise we increase usage of remaining time as the game goes on
else
{
double k = 1 + 20 * moveNum / (500.0 + moveNum);
ratio = (type == OptimumTime ? 0.017 : 0.07) * (k + inc / myTime);
}
const double TMaxRatio = (T == OptimumTime ? 1 : MaxRatio);
const double TStealRatio = (T == OptimumTime ? 0 : StealRatio);
int time = int(std::min(1.0, ratio) * std::max(0, myTime - moveOverhead));
double moveImportance = (move_importance(ply) * slowMover) / 100;
double otherMovesImportance = 0;
if (type == OptimumTime && ponder)
time = 5 * time / 4;
for (int i = 1; i < movesToGo; ++i)
otherMovesImportance += move_importance(ply + 2 * i);
double ratio1 = (TMaxRatio * moveImportance) / (TMaxRatio * moveImportance + otherMovesImportance);
double ratio2 = (moveImportance + TStealRatio * otherMovesImportance) / (moveImportance + otherMovesImportance);
return int(myTime * std::min(ratio1, ratio2)); // Intel C++ asks for an explicit cast
return time;
}
} // namespace
@@ -81,12 +81,11 @@ namespace {
/// inc > 0 && movestogo == 0 means: x basetime + z increment
/// inc > 0 && movestogo != 0 means: x moves in y minutes + z increment
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"];
void TimeManagement::init(Search::LimitsType& limits, Color us, int ply)
{
int moveOverhead = Options["Move Overhead"];
int npmsec = Options["nodestime"];
bool ponder = Options["Ponder"];
// If we have to play in 'nodes as time' mode, then convert from time
// to nodes, and use resulting values in time management formulas.
@@ -103,30 +102,11 @@ void TimeManagement::init(Search::LimitsType& limits, Color us, int ply) {
limits.npmsec = npmsec;
}
int moveNum = (ply + 1) / 2;
startTime = limits.startTime;
optimumTime = maximumTime = 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)
{
// 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);
int t1 = minThinkingTime + remaining<OptimumTime>(hypMyTime, hypMTG, ply, slowMover);
int t2 = minThinkingTime + remaining<MaxTime >(hypMyTime, hypMTG, ply, slowMover);
optimumTime = std::min(t1, optimumTime);
maximumTime = std::min(t2, maximumTime);
}
if (Options["Ponder"])
optimumTime += optimumTime / 4;
optimumTime = remaining(limits.time[us], limits.inc[us], moveOverhead,
limits.movestogo, moveNum, ponder, OptimumTime);
maximumTime = remaining(limits.time[us], limits.inc[us], moveOverhead,
limits.movestogo, moveNum, ponder, MaxTime);
}