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Adjust time used for move based on previous score

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Use less time if evaluation is not worse than for previous move and even less time if in addition no fail low encountered for current iteration.

STC: 10+0.1
ELO: 5.37 +-2.9 (95%) LOS: 100.0%
Total: 20000 W: 3832 L: 3523 D: 12645

STC: 10+0.1
LLR: 2.96 (-2.94,2.94) [0.00,5.00]
Total: 17527 W: 3334 L: 3132 D: 11061

LTC: 60+0.6
LLR: 2.95 (-2.94,2.94) [0.00,5.00]
Total: 28233 W: 3939 L: 3725 D: 20569

LTC: 60+0.6
ELO: 2.43 +-1.4 (95%) LOS: 100.0%
Total: 60000 W: 8266 L: 7847 D: 43887

LTC: 60+0.06
LLR: 2.95 (-2.94,2.94) [-1.00,3.00]
Total: 38932 W: 5408 L: 5207 D: 28317

Resolves #547
This commit is contained in:
Leonid Pechenik
2016-01-03 14:00:56 +00:00
committed by Joona Kiiski
parent 5972c4a678
commit 9eceb894ac
5 changed files with 18 additions and 11 deletions
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10
src/timeman.cpp
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@@ -33,8 +33,8 @@ namespace {
enum TimeType { OptimumTime, MaxTime };
const int MoveHorizon = 50; // Plan time management at most this many moves ahead
const double MaxRatio = 6.93; // When in trouble, we can step over reserved time with this ratio
const double StealRatio = 0.36; // However we must not steal time from remaining moves over 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 a skew-logistic function based on naive statistical
@@ -44,9 +44,9 @@ namespace {
double move_importance(int ply) {
const double XScale = 8.27;
const double XShift = 59.;
const double Skew = 0.179;
const double XScale = 7.64;
const double XShift = 58.4;
const double Skew = 0.183;
return pow((1 + exp((ply - XShift) / XScale)), -Skew) + DBL_MIN; // Ensure non-zero
}