namespace {
-
// Threshold for lazy and space evaluation
constexpr Value LazyThreshold1 = Value(3631);
constexpr Value LazyThreshold2 = Value(2084);
Value Eval::evaluate(const Position& pos) {
Value v;
- bool useClassical = false;
+ // Deciding between classical and NNUE eval (~10 Elo): for high PSQ imbalance we use classical,
+ // but we switch to NNUE during long shuffling or with high material on the board.
+ bool useClassical = (pos.this_thread()->depth > 9 || pos.count<ALL_PIECES>() > 7) &&
+ abs(eg_value(pos.psq_score())) * 5 > (856 + pos.non_pawn_material() / 64) * (10 + pos.rule50_count());
// Deciding between classical and NNUE eval (~10 Elo): for high PSQ imbalance we use classical,
// but we switch to NNUE during long shuffling or with high material on the board.
- if ( !useNNUE
- || ((pos.this_thread()->depth > 9 || pos.count<ALL_PIECES>() > 7) &&
- abs(eg_value(pos.psq_score())) * 5 > (856 + pos.non_pawn_material() / 64) * (10 + pos.rule50_count())))
+ if (!useNNUE || useClassical)
{
v = Evaluation<NO_TRACE>(pos).value(); // classical
useClassical = abs(v) >= 297;
// If result of a classical evaluation is much lower than threshold fall back to NNUE
if (useNNUE && !useClassical)
{
- Value nnue = NNUE::evaluate(pos, true); // NNUE
- int scale = 1014 + 21 * pos.non_pawn_material() / 1024;
+ int complexity;
+ int scale = 1048 + 109 * pos.non_pawn_material() / 5120;
Color stm = pos.side_to_move();
Value optimism = pos.this_thread()->optimism[stm];
Value psq = (stm == WHITE ? 1 : -1) * eg_value(pos.psq_score());
- int complexity = 35 * abs(nnue - psq) / 256;
+ Value nnue = NNUE::evaluate(pos, true, &complexity); // NNUE
- optimism = optimism * (32 + complexity) / 32;
- v = (nnue * scale + optimism * (scale - 846)) / 1024;
+ complexity = (137 * complexity + 137 * abs(nnue - psq)) / 256;
+ optimism = optimism * (255 + complexity) / 256;
+ v = (nnue * scale + optimism * (scale - 848)) / 1024;
if (pos.is_chess960())
v += fix_FRC(pos);