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Introduce mean squared score for delta adjustments

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This patch introduces the value `meanSquaredScore`, which makes the
initial delta sensitive to unstable iterative deepening scores.

Passed STC:
https://tests.stockfishchess.org/tests/view/66fed74286d5ee47d953bb42
LLR: 2.98 (-2.94,2.94) <0.00,2.00>
Total: 71104 W: 18635 L: 18262 D: 34207
Ptnml(0-2): 234, 8365, 17993, 8714, 246

Passed LTC:
https://tests.stockfishchess.org/tests/view/6700088e86d5ee47d953bbe9
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 212544 W: 54238 L: 53560 D: 104746
Ptnml(0-2): 120, 23093, 59172, 23763, 124

closes https://github.com/official-stockfish/Stockfish/pull/5627

Bench: 1395505
This commit is contained in:
Nonlinear2 2024-10-09 20:00:19 +02:00 • committed by Disservin
parent d4358ddba7
commit aaadbe0572
2 changed files with 16 additions and 11 deletions
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6
src/search.cpp
View file

@ -312,8 +312,8 @@ void Search::Worker::iterative_deepening() {
selDepth = 0; selDepth = 0;
// Reset aspiration window starting size // Reset aspiration window starting size
delta = 5 + std::abs(rootMoves[pvIdx].meanSquaredScore) / 13797;
Value avg = rootMoves[pvIdx].averageScore; Value avg = rootMoves[pvIdx].averageScore;
delta = 5 + avg * avg / 11797;
alpha = std::max(avg - delta, -VALUE_INFINITE); alpha = std::max(avg - delta, -VALUE_INFINITE);
beta = std::min(avg + delta, VALUE_INFINITE); beta = std::min(avg + delta, VALUE_INFINITE);
@ -1265,6 +1265,10 @@ moves_loop: // When in check, search starts here
rm.averageScore = rm.averageScore =
rm.averageScore != -VALUE_INFINITE ? (value + rm.averageScore) / 2 : value; rm.averageScore != -VALUE_INFINITE ? (value + rm.averageScore) / 2 : value;
rm.meanSquaredScore = rm.meanSquaredScore != -VALUE_INFINITE * VALUE_INFINITE
? (value * std::abs(value) + rm.meanSquaredScore) / 2
: value * std::abs(value);
// PV move or new best move? // PV move or new best move?
if (moveCount == 1 || value > alpha) if (moveCount == 1 || value > alpha)
{ {

1
src/search.h
View file

@ -95,6 +95,7 @@ struct RootMove {
Value score = -VALUE_INFINITE; Value score = -VALUE_INFINITE;
Value previousScore = -VALUE_INFINITE; Value previousScore = -VALUE_INFINITE;
Value averageScore = -VALUE_INFINITE; Value averageScore = -VALUE_INFINITE;
Value meanSquaredScore = -VALUE_INFINITE * VALUE_INFINITE;
Value uciScore = -VALUE_INFINITE; Value uciScore = -VALUE_INFINITE;
bool scoreLowerbound = false; bool scoreLowerbound = false;
bool scoreUpperbound = false; bool scoreUpperbound = false;