// Early exit if score is high
auto lazy_skip = [&](Value lazyThreshold) {
- return abs(mg_value(score) + eg_value(score)) > lazyThreshold + pos.non_pawn_material() / 32;
+ return abs(mg_value(score) + eg_value(score)) > lazyThreshold
+ + std::abs(pos.this_thread()->bestValue) * 5 / 4
+ + pos.non_pawn_material() / 32;
};
if (lazy_skip(LazyThreshold1))
v = Evaluation<NO_TRACE>(pos).value(); // classical
else
{
- int scale = 883
- + 32 * pos.count<PAWN>()
- + 32 * pos.non_pawn_material() / 1024;
+ int scale = 898
+ + 24 * pos.count<PAWN>()
+ + 33 * pos.non_pawn_material() / 1024;
v = NNUE::evaluate(pos, true) * scale / 1024; // NNUE
}
// Damp down the evaluation linearly when shuffling
- v = v * (100 - pos.rule50_count()) / 100;
+ v = v * (207 - pos.rule50_count()) / 207;
// Guarantee evaluation does not hit the tablebase range
v = std::clamp(v, VALUE_TB_LOSS_IN_MAX_PLY + 1, VALUE_TB_WIN_IN_MAX_PLY - 1);
std::memset(scores, 0, sizeof(scores));
pos.this_thread()->trend = SCORE_ZERO; // Reset any dynamic contempt
+ pos.this_thread()->bestValue = VALUE_ZERO; // Reset bestValue for lazyEval
v = Evaluation<TRACE>(pos).value();