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doEvenDeeperSearch + tuning
Credit for the main idea of doEvenDeeperSearch goes to Vizvezdenec, tuning by FauziAkram: Expansion of existing logic of doDeeperSearch - if value from LMR is really really good do full depth search not 1 ply deeper but rather 2 instead. Passed STC: LLR: 2.93 (-2.94,2.94) <0.00,2.00> Total: 330048 W: 87672 L: 86942 D: 155434 Ptnml(0-2): 1012, 36739, 88912, 37229, 1132 https://tests.stockfishchess.org/tests/view/638a1cadd2b9c924c4c621d2 Passed LTC: LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 216696 W: 57891 L: 57240 D: 101565 Ptnml(0-2): 72, 21221, 65152, 21790, 113 https://tests.stockfishchess.org/tests/view/638c7d52a971f1f096c68fe2 closes https://github.com/official-stockfish/Stockfish/pull/4256 Bench: 3461830
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2 changed files with 11 additions and 10 deletions
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@ -1063,7 +1063,7 @@ Value Eval::evaluate(const Position& pos, int* complexity) {
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else
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{
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int nnueComplexity;
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int scale = 1064 + 106 * pos.non_pawn_material() / 5120;
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int scale = 1076 + 96 * pos.non_pawn_material() / 5120;
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Color stm = pos.side_to_move();
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Value optimism = pos.this_thread()->optimism[stm];
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@ -1071,21 +1071,21 @@ Value Eval::evaluate(const Position& pos, int* complexity) {
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Value nnue = NNUE::evaluate(pos, true, &nnueComplexity);
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// Blend nnue complexity with (semi)classical complexity
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nnueComplexity = ( 416 * nnueComplexity
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+ 424 * abs(psq - nnue)
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nnueComplexity = ( 412 * nnueComplexity
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+ 428 * abs(psq - nnue)
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+ (optimism > 0 ? int(optimism) * int(psq - nnue) : 0)
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) / 1024;
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) / 1026;
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// Return hybrid NNUE complexity to caller
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if (complexity)
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*complexity = nnueComplexity;
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optimism = optimism * (269 + nnueComplexity) / 256;
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v = (nnue * scale + optimism * (scale - 754)) / 1024;
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optimism = optimism * (278 + nnueComplexity) / 256;
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v = (nnue * scale + optimism * (scale - 755)) / 1024;
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}
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// Damp down the evaluation linearly when shuffling
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v = v * (195 - pos.rule50_count()) / 211;
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v = v * (197 - pos.rule50_count()) / 214;
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// Guarantee evaluation does not hit the tablebase range
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v = std::clamp(v, VALUE_TB_LOSS_IN_MAX_PLY + 1, VALUE_TB_WIN_IN_MAX_PLY - 1);
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@ -81,7 +81,7 @@ namespace {
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// History and stats update bonus, based on depth
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int stat_bonus(Depth d) {
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return std::min((12 * d + 282) * d - 349 , 1594);
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return std::min((12 * d + 282) * d - 349 , 1480);
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}
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// Add a small random component to draw evaluations to avoid 3-fold blindness
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@ -1172,7 +1172,7 @@ moves_loop: // When in check, search starts here
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- 4433;
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// Decrease/increase reduction for moves with a good/bad history (~30 Elo)
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r -= ss->statScore / (13628 + 4000 * (depth > 7 && depth < 19));
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r -= ss->statScore / (13000 + 4152 * (depth > 7 && depth < 19));
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// In general we want to cap the LMR depth search at newDepth, but when
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// reduction is negative, we allow this move a limited search extension
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@ -1187,9 +1187,10 @@ moves_loop: // When in check, search starts here
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// Adjust full depth search based on LMR results - if result
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// was good enough search deeper, if it was bad enough search shallower
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const bool doDeeperSearch = value > (alpha + 64 + 11 * (newDepth - d));
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const bool doEvenDeeperSearch = value > alpha + 582;
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const bool doShallowerSearch = value < bestValue + newDepth;
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newDepth += doDeeperSearch - doShallowerSearch;
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newDepth += doDeeperSearch - doShallowerSearch + doEvenDeeperSearch;
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if (newDepth > d)
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value = -search<NonPV>(pos, ss+1, -(alpha+1), -alpha, newDepth, !cutNode);
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