Tune a few parameters related to evaluation

based on a SPSA tune (using Autoselect)
https://tests.stockfishchess.org/tests/view/61d5aa63a314fed318a57046

passed STC:
LLR: 2.93 (-2.94,2.94) <0.00,2.50>
Total: 61960 W: 16640 L: 16316 D: 29004
Ptnml(0-2): 278, 6934, 16204, 7314, 250
https://tests.stockfishchess.org/tests/view/61d7fe4af5fd40f357469a8d

passed LTC:
LLR: 2.97 (-2.94,2.94) <0.50,3.00>
Total: 79408 W: 21994 L: 21618 D: 35796
Ptnml(0-2): 106, 7887, 23331, 8285, 95
https://tests.stockfishchess.org/tests/view/61d836b7f5fd40f35746a3d5

closes #3883

Bench: 4266621

src/evaluate.cpp

@@ -192,8 +192,8 @@ using namespace Trace;
 namespace {
 
  // Threshold for lazy and space evaluation
- constexpr Value LazyThreshold1 = Value(3130);
- constexpr Value LazyThreshold2 = Value(2204);
+ constexpr Value LazyThreshold1 = Value(3631);
+ constexpr Value LazyThreshold2 = Value(2084);
  constexpr Value SpaceThreshold = Value(11551);
 
  // KingAttackWeights[PieceType] contains king attack weights by piece type
@@ -1087,10 +1087,10 @@ Value Eval::evaluate(const Position& pos) {
  // 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
- || abs(eg_value(pos.psq_score())) * 5 > (850 + pos.non_pawn_material() / 64) * (5 + pos.rule50_count()))
+ || abs(eg_value(pos.psq_score())) * 5 > (849 + pos.non_pawn_material() / 64) * (5 + pos.rule50_count()))
  {
  v = Evaluation<NO_TRACE>(pos).value(); // classical
- useClassical = abs(v) >= 300;
+ useClassical = abs(v) >= 298;
  }
 
  // If result of a classical evaluation is much lower than threshold fall back to NNUE
@@ -1101,17 +1101,17 @@ Value Eval::evaluate(const Position& pos) {
  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 = abs(nnue - psq) / 256;
+ int complexity = 35 * abs(nnue - psq) / 256;
 
- optimism *= (1 + complexity);
+ optimism = optimism * (44 + complexity) / 32;
  v = (nnue + optimism) * scale / 1024 - optimism;
 
  if (pos.is_chess960())
  v += fix_FRC(pos);
  }
 
  // Damp down the evaluation linearly when shuffling
- v = v * (207 - pos.rule50_count()) / 207;
+ v = v * (208 - pos.rule50_count()) / 208;
 
  // 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);