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
+ Value nnue = NNUE::evaluate(pos, true); // NNUE
+ Color stm = pos.side_to_move();
+ Value optimism = pos.this_thread()->optimism[stm];
+
+ v = (nnue + optimism) * scale / 1024 - optimism;
if (pos.is_chess960())
v += fix_FRC(pos);
}
// 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
+ // Reset any global variable used in eval
+ pos.this_thread()->trend = SCORE_ZERO;
+ pos.this_thread()->bestValue = VALUE_ZERO;
+ pos.this_thread()->optimism[WHITE] = VALUE_ZERO;
+ pos.this_thread()->optimism[BLACK] = VALUE_ZERO;
v = Evaluation<TRACE>(pos).value();