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VVLTC Search Tune
A single tuning run of 190k games was conducted: https://tests.stockfishchess.org/tests/view/670f3e3786d5ee47d953c554. Passed VVLTC 1st sprt: https://tests.stockfishchess.org/tests/view/672344dc86d5ee47d953d8c3 LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 56768 W: 14615 L: 14323 D: 27830 Ptnml(0-2): 3, 5152, 17789, 5430, 10 Passed VVLTC 2nd sprt (rebased): https://tests.stockfishchess.org/tests/view/6726d83786d5ee47d953db03 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 57884 W: 14885 L: 14554 D: 28445 Ptnml(0-2): 5, 5300, 17999, 5635, 3 closes https://github.com/official-stockfish/Stockfish/pull/5669 Bench: 920336
This commit is contained in:
parent
cc5c67c564
commit
3d084e9164
1 changed files with 51 additions and 51 deletions
102
src/search.cpp
102
src/search.cpp
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@ -67,7 +67,7 @@ namespace {
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// Futility margin
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Value futility_margin(Depth d, bool noTtCutNode, bool improving, bool oppWorsening) {
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Value futilityMult = 118 - 33 * noTtCutNode;
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Value futilityMult = 109 - 27 * noTtCutNode;
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Value improvingDeduction = improving * futilityMult * 2;
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Value worseningDeduction = oppWorsening * futilityMult / 3;
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@ -94,16 +94,16 @@ Value to_corrected_static_eval(Value v, const Worker& w, const Position& pos, St
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cntcv = int((*(ss - 2)->continuationCorrectionHistory)[pos.piece_on(m.to_sq())][m.to_sq()]);
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const auto cv =
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(5932 * pcv + 3269 * macv + 5660 * micv + 6666 * (wnpcv + bnpcv) + 5555 * cntcv) / 131072;
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(6384 * pcv + 3583 * macv + 6492 * micv + 6725 * (wnpcv + bnpcv) + cntcv * 5880) / 131072;
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v += cv;
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return std::clamp(v, VALUE_TB_LOSS_IN_MAX_PLY + 1, VALUE_TB_WIN_IN_MAX_PLY - 1);
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}
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// History and stats update bonus, based on depth
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int stat_bonus(Depth d) { return std::min(179 * d - 108, 1598); }
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int stat_bonus(Depth d) { return std::min(168 * d - 100, 1718); }
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// History and stats update malus, based on depth
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int stat_malus(Depth d) { return std::min(820 * d - 261, 2246); }
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int stat_malus(Depth d) { return std::min(768 * d - 257, 2351); }
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// Add a small random component to draw evaluations to avoid 3-fold blindness
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Value value_draw(size_t nodes) { return VALUE_DRAW - 1 + Value(nodes & 0x2); }
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@ -311,13 +311,13 @@ void Search::Worker::iterative_deepening() {
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selDepth = 0;
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// Reset aspiration window starting size
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delta = 5 + std::abs(rootMoves[pvIdx].meanSquaredScore) / 13797;
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delta = 5 + std::abs(rootMoves[pvIdx].meanSquaredScore) / 13461;
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Value avg = rootMoves[pvIdx].averageScore;
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alpha = std::max(avg - delta, -VALUE_INFINITE);
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beta = std::min(avg + delta, VALUE_INFINITE);
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// Adjust optimism based on root move's averageScore (~4 Elo)
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optimism[us] = 132 * avg / (std::abs(avg) + 89);
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optimism[us] = 150 * avg / (std::abs(avg) + 85);
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optimism[~us] = -optimism[us];
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// Start with a small aspiration window and, in the case of a fail
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@ -502,8 +502,8 @@ void Search::Worker::iterative_deepening() {
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void Search::Worker::clear() {
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mainHistory.fill(0);
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lowPlyHistory.fill(0);
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captureHistory.fill(-753);
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pawnHistory.fill(-1152);
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captureHistory.fill(-758);
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pawnHistory.fill(-1158);
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pawnCorrectionHistory.fill(0);
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majorPieceCorrectionHistory.fill(0);
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minorPieceCorrectionHistory.fill(0);
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@ -518,10 +518,10 @@ void Search::Worker::clear() {
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for (StatsType c : {NoCaptures, Captures})
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for (auto& to : continuationHistory[inCheck][c])
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for (auto& h : to)
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h->fill(-678);
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h->fill(-645);
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for (size_t i = 1; i < reductions.size(); ++i)
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reductions[i] = int((18.43 + std::log(size_t(options["Threads"])) / 2) * std::log(i));
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reductions[i] = int((19.43 + std::log(size_t(options["Threads"])) / 2) * std::log(i));
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refreshTable.clear(networks[numaAccessToken]);
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}
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@ -760,7 +760,7 @@ Value Search::Worker::search(
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// Use static evaluation difference to improve quiet move ordering (~9 Elo)
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if (((ss - 1)->currentMove).is_ok() && !(ss - 1)->inCheck && !priorCapture)
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{
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int bonus = std::clamp(-10 * int((ss - 1)->staticEval + ss->staticEval), -1641, 1423) + 760;
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int bonus = std::clamp(-10 * int((ss - 1)->staticEval + ss->staticEval), -1831, 1428) + 623;
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thisThread->mainHistory[~us][((ss - 1)->currentMove).from_to()] << bonus;
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if (type_of(pos.piece_on(prevSq)) != PAWN && ((ss - 1)->currentMove).type_of() != PROMOTION)
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thisThread->pawnHistory[pawn_structure_index(pos)][pos.piece_on(prevSq)][prevSq]
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@ -778,7 +778,7 @@ Value Search::Worker::search(
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// Step 7. Razoring (~1 Elo)
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// If eval is really low, check with qsearch if we can exceed alpha. If the
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// search suggests we cannot exceed alpha, return a speculative fail low.
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if (eval < alpha - 501 - 272 * depth * depth)
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if (eval < alpha - 469 - 307 * depth * depth)
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{
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value = qsearch<NonPV>(pos, ss, alpha - 1, alpha);
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if (value < alpha && std::abs(value) < VALUE_TB_WIN_IN_MAX_PLY)
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@ -787,9 +787,9 @@ Value Search::Worker::search(
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// Step 8. Futility pruning: child node (~40 Elo)
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// The depth condition is important for mate finding.
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if (!ss->ttPv && depth < 13
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if (!ss->ttPv && depth < 14
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&& eval - futility_margin(depth, cutNode && !ss->ttHit, improving, opponentWorsening)
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- (ss - 1)->statScore / 272
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- (ss - 1)->statScore / 290
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>= beta
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&& eval >= beta && (!ttData.move || ttCapture) && beta > VALUE_TB_LOSS_IN_MAX_PLY
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&& eval < VALUE_TB_WIN_IN_MAX_PLY)
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@ -799,13 +799,13 @@ Value Search::Worker::search(
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// Step 9. Null move search with verification search (~35 Elo)
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if (cutNode && (ss - 1)->currentMove != Move::null() && eval >= beta
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&& ss->staticEval >= beta - 23 * depth + 400 && !excludedMove && pos.non_pawn_material(us)
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&& ss->staticEval >= beta - 21 * depth + 421 && !excludedMove && pos.non_pawn_material(us)
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&& ss->ply >= thisThread->nmpMinPly && beta > VALUE_TB_LOSS_IN_MAX_PLY)
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{
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assert(eval - beta >= 0);
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// Null move dynamic reduction based on depth and eval
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Depth R = std::min(int(eval - beta) / 209, 6) + depth / 3 + 5;
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Depth R = std::min(int(eval - beta) / 235, 7) + depth / 3 + 5;
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ss->currentMove = Move::null();
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ss->continuationHistory = &thisThread->continuationHistory[0][0][NO_PIECE][0];
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@ -855,7 +855,7 @@ Value Search::Worker::search(
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// Step 11. ProbCut (~10 Elo)
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// If we have a good enough capture (or queen promotion) and a reduced search
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// returns a value much above beta, we can (almost) safely prune the previous move.
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probCutBeta = beta + 189 - 53 * improving - 30 * opponentWorsening;
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probCutBeta = beta + 187 - 53 * improving - 27 * opponentWorsening;
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if (!PvNode && depth > 3
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&& std::abs(beta) < VALUE_TB_WIN_IN_MAX_PLY
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// If value from transposition table is lower than probCutBeta, don't attempt
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@ -926,7 +926,7 @@ Value Search::Worker::search(
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moves_loop: // When in check, search starts here
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// Step 12. A small Probcut idea (~4 Elo)
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probCutBeta = beta + 379;
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probCutBeta = beta + 417;
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if ((ttData.bound & BOUND_LOWER) && ttData.depth >= depth - 4 && ttData.value >= probCutBeta
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&& std::abs(beta) < VALUE_TB_WIN_IN_MAX_PLY
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&& std::abs(ttData.value) < VALUE_TB_WIN_IN_MAX_PLY)
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@ -1010,15 +1010,15 @@ moves_loop: // When in check, search starts here
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// Futility pruning for captures (~2 Elo)
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if (!givesCheck && lmrDepth < 7 && !ss->inCheck)
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{
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Value futilityValue = ss->staticEval + 300 + 238 * lmrDepth
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Value futilityValue = ss->staticEval + 287 + 253 * lmrDepth
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+ PieceValue[capturedPiece] + captHist / 7;
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if (futilityValue <= alpha)
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continue;
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}
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// SEE based pruning for captures and checks (~11 Elo)
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int seeHist = std::clamp(captHist / 32, -159 * depth, 160 * depth);
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if (!pos.see_ge(move, -167 * depth - seeHist))
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int seeHist = std::clamp(captHist / 33, -161 * depth, 156 * depth);
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if (!pos.see_ge(move, -162 * depth - seeHist))
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continue;
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}
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else
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+ thisThread->pawnHistory[pawn_structure_index(pos)][movedPiece][move.to_sq()];
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// Continuation history based pruning (~2 Elo)
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if (history < -4071 * depth)
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if (history < -3884 * depth)
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continue;
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history += 2 * thisThread->mainHistory[us][move.from_to()];
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lmrDepth += history / 3653;
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lmrDepth += history / 3609;
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Value futilityValue =
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ss->staticEval + (bestValue < ss->staticEval - 51 ? 145 : 49) + 144 * lmrDepth;
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ss->staticEval + (bestValue < ss->staticEval - 45 ? 140 : 43) + 141 * lmrDepth;
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// Futility pruning: parent node (~13 Elo)
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if (!ss->inCheck && lmrDepth < 12 && futilityValue <= alpha)
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lmrDepth = std::max(lmrDepth, 0);
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// Prune moves with negative SEE (~4 Elo)
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if (!pos.see_ge(move, -24 * lmrDepth * lmrDepth))
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if (!pos.see_ge(move, -25 * lmrDepth * lmrDepth))
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continue;
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}
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}
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// and lower extension margins scale well.
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if (!rootNode && move == ttData.move && !excludedMove
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&& depth >= 4 - (thisThread->completedDepth > 36) + ss->ttPv
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&& depth >= 4 - (thisThread->completedDepth > 33) + ss->ttPv
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&& std::abs(ttData.value) < VALUE_TB_WIN_IN_MAX_PLY && (ttData.bound & BOUND_LOWER)
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&& ttData.depth >= depth - 3)
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{
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Value singularBeta = ttData.value - (54 + 77 * (ss->ttPv && !PvNode)) * depth / 64;
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Value singularBeta = ttData.value - (56 + 79 * (ss->ttPv && !PvNode)) * depth / 64;
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Depth singularDepth = newDepth / 2;
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ss->excludedMove = move;
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if (value < singularBeta)
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{
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int doubleMargin = 262 * PvNode - 204 * !ttCapture;
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int tripleMargin = 97 + 266 * PvNode - 255 * !ttCapture + 94 * ss->ttPv;
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int doubleMargin = 249 * PvNode - 194 * !ttCapture;
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int tripleMargin = 94 + 287 * PvNode - 249 * !ttCapture + 99 * ss->ttPv;
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extension = 1 + (value < singularBeta - doubleMargin)
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+ (value < singularBeta - tripleMargin);
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else if (PvNode && move.to_sq() == prevSq
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&& thisThread->captureHistory[movedPiece][move.to_sq()]
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[type_of(pos.piece_on(move.to_sq()))]
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> 4299)
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> 4321)
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extension = 1;
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}
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@ -1182,7 +1182,7 @@ moves_loop: // When in check, search starts here
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ss->statScore = 2 * thisThread->mainHistory[us][move.from_to()]
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+ (*contHist[0])[movedPiece][move.to_sq()]
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+ (*contHist[1])[movedPiece][move.to_sq()] - 4410;
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+ (*contHist[1])[movedPiece][move.to_sq()] - 3996;
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// Decrease/increase reduction for moves with a good/bad history (~8 Elo)
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r -= ss->statScore * 1287 / 16384;
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{
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// Adjust full-depth search based on LMR results - if the result was
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// good enough search deeper, if it was bad enough search shallower.
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const bool doDeeperSearch = value > (bestValue + 38 + 2 * newDepth); // (~1 Elo)
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const bool doShallowerSearch = value < bestValue + 8; // (~2 Elo)
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const bool doDeeperSearch = value > (bestValue + 42 + 2 * newDepth); // (~1 Elo)
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const bool doShallowerSearch = value < bestValue + 10; // (~2 Elo)
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newDepth += doDeeperSearch - doShallowerSearch;
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// Bonus for prior countermove that caused the fail low
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else if (!priorCapture && prevSq != SQ_NONE)
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{
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int bonus = (118 * (depth > 5) + 38 * !allNode + 169 * ((ss - 1)->moveCount > 8)
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+ 116 * (!ss->inCheck && bestValue <= ss->staticEval - 101)
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+ 133 * (!(ss - 1)->inCheck && bestValue <= -(ss - 1)->staticEval - 92));
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int bonus = (117 * (depth > 5) + 39 * !allNode + 168 * ((ss - 1)->moveCount > 8)
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+ 115 * (!ss->inCheck && bestValue <= ss->staticEval - 108)
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+ 119 * (!(ss - 1)->inCheck && bestValue <= -(ss - 1)->staticEval - 83));
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// Proportional to "how much damage we have to undo"
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bonus += std::min(-(ss - 1)->statScore / 102, 305);
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bonus += std::min(-(ss - 1)->statScore / 113, 300);
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bonus = std::max(bonus, 0);
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update_continuation_histories(ss - 1, pos.piece_on(prevSq), prevSq,
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stat_bonus(depth) * bonus / 107);
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stat_bonus(depth) * bonus / 93);
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thisThread->mainHistory[~us][((ss - 1)->currentMove).from_to()]
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<< stat_bonus(depth) * bonus / 174;
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<< stat_bonus(depth) * bonus / 179;
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if (type_of(pos.piece_on(prevSq)) != PAWN && ((ss - 1)->currentMove).type_of() != PROMOTION)
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thisThread->pawnHistory[pawn_structure_index(pos)][pos.piece_on(prevSq)][prevSq]
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<< stat_bonus(depth) * bonus / 25;
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<< stat_bonus(depth) * bonus / 24;
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}
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// Bonus when search fails low and there is a TT move
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else if (ttData.move && !allNode)
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thisThread->mainHistory[us][ttData.move.from_to()] << stat_bonus(depth) / 4;
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thisThread->mainHistory[us][ttData.move.from_to()] << stat_bonus(depth) * 23 / 100;
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if (PvNode)
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bestValue = std::min(bestValue, maxValue);
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auto bonus = std::clamp(int(bestValue - ss->staticEval) * depth / 8,
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-CORRECTION_HISTORY_LIMIT / 4, CORRECTION_HISTORY_LIMIT / 4);
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thisThread->pawnCorrectionHistory[us][pawn_structure_index<Correction>(pos)]
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<< bonus * 101 / 128;
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thisThread->majorPieceCorrectionHistory[us][major_piece_index(pos)] << bonus * 157 / 128;
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thisThread->minorPieceCorrectionHistory[us][minor_piece_index(pos)] << bonus * 153 / 128;
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<< bonus * 107 / 128;
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thisThread->majorPieceCorrectionHistory[us][major_piece_index(pos)] << bonus * 162 / 128;
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thisThread->minorPieceCorrectionHistory[us][minor_piece_index(pos)] << bonus * 148 / 128;
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thisThread->nonPawnCorrectionHistory[WHITE][us][non_pawn_index<WHITE>(pos)]
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<< bonus * 123 / 128;
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<< bonus * 122 / 128;
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thisThread->nonPawnCorrectionHistory[BLACK][us][non_pawn_index<BLACK>(pos)]
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<< bonus * 165 / 128;
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<< bonus * 185 / 128;
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if (m.is_ok())
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(*(ss - 2)->continuationCorrectionHistory)[pos.piece_on(m.to_sq())][m.to_sq()] << bonus;
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@ -1566,7 +1566,7 @@ Value Search::Worker::qsearch(Position& pos, Stack* ss, Value alpha, Value beta)
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if (bestValue > alpha)
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alpha = bestValue;
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futilityBase = ss->staticEval + 280;
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futilityBase = ss->staticEval + 306;
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}
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const PieceToHistory* contHist[] = {(ss - 1)->continuationHistory,
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@ -1629,11 +1629,11 @@ Value Search::Worker::qsearch(Position& pos, Stack* ss, Value alpha, Value beta)
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+ (*contHist[1])[pos.moved_piece(move)][move.to_sq()]
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+ thisThread->pawnHistory[pawn_structure_index(pos)][pos.moved_piece(move)]
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[move.to_sq()]
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<= 5036)
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<= 5095)
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continue;
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// Do not search moves with bad enough SEE values (~5 Elo)
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if (!pos.see_ge(move, -82))
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if (!pos.see_ge(move, -83))
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continue;
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}
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@ -1701,7 +1701,7 @@ Value Search::Worker::qsearch(Position& pos, Stack* ss, Value alpha, Value beta)
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Depth Search::Worker::reduction(bool i, Depth d, int mn, int delta) const {
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int reductionScale = reductions[d] * reductions[mn];
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return (reductionScale + 1239 - delta * 795 / rootDelta) + (!i && reductionScale > 1341) * 1135;
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return (reductionScale + 1304 - delta * 814 / rootDelta) + (!i && reductionScale > 1423) * 1135;
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}
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// elapsed() returns the time elapsed since the search started. If the
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@ -1832,7 +1832,7 @@ void update_all_stats(const Position& pos,
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// at ply -1, -2, -3, -4, and -6 with current move.
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void update_continuation_histories(Stack* ss, Piece pc, Square to, int bonus) {
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bonus = bonus * 53 / 64;
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bonus = bonus * 50 / 64;
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for (int i : {1, 2, 3, 4, 6})
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{
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