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 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
- // move_importance() is an exponential function based on naive observation
- // that a game is closer to be decided after each half-move. This function
- // should be decreasing and with "nice" convexity properties.
+ // 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 move_importance(int ply) {
- const double PlyScale = 109.3265;
- const double PlyGrowth = 4.0;
+ const double XScale = 7.64;
+ const double XShift = 58.4;
+ const double Skew = 0.183;
- return exp(-pow(ply / PlyScale, PlyGrowth)) + DBL_MIN; // Ensure non-zero
+ return pow((1 + exp((ply - XShift) / XScale)), -Skew) + DBL_MIN; // Ensure non-zero
}
template<TimeType T>
- int remaining(int myTime, int movesToGo, int ply)
+ int remaining(int myTime, int movesToGo, int ply, int slowMover)
{
const double TMaxRatio = (T == OptimumTime ? 1 : MaxRatio);
const double TStealRatio = (T == OptimumTime ? 0 : StealRatio);
- double moveImportance = move_importance(ply);
+ double moveImportance = (move_importance(ply) * slowMover) / 100;
double otherMovesImportance = 0;
for (int i = 1; i < movesToGo; ++i)
{
int minThinkingTime = Options["Minimum Thinking Time"];
int moveOverhead = Options["Move Overhead"];
+ int slowMover = Options["Slow Mover"];
int npmsec = Options["nodestime"];
// If we have to play in 'nodes as time' mode, then convert from time
hypMyTime = std::max(hypMyTime, 0);
- int t1 = minThinkingTime + remaining<OptimumTime>(hypMyTime, hypMTG, ply);
- int t2 = minThinkingTime + remaining<MaxTime >(hypMyTime, hypMTG, ply);
+ 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);