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VLTC time management tune
Result of 35k games of SPSA tuning at 180+1.8. Tuning attempt can be found here: https://tests.stockfishchess.org/tests/view/65e40599f2ef6c733362b03b Passed VLTC 180+1.8: https://tests.stockfishchess.org/tests/view/65e5a6f5416ecd92c162b5d4 LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 31950 W: 8225 L: 7949 D: 15776 Ptnml(0-2): 3, 3195, 9309, 3459, 9 Passed VLTC 240+2.4: https://tests.stockfishchess.org/tests/view/65e714de0ec64f0526c3d1f1 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 65108 W: 16558 L: 16202 D: 32348 Ptnml(0-2): 7, 6366, 19449, 6728, 4 closes https://github.com/official-stockfish/Stockfish/pull/5095 Bench: 1714391
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2 changed files with 17 additions and 17 deletions
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@ -429,15 +429,15 @@ void Search::Worker::iterative_deepening() {
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int nodesEffort = effort[bestmove.from_sq()][bestmove.to_sq()] * 100
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/ std::max(size_t(1), size_t(nodes));
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double fallingEval = (66 + 14 * (mainThread->bestPreviousAverageScore - bestValue)
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+ 6 * (mainThread->iterValue[iterIdx] - bestValue))
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/ 616.6;
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fallingEval = std::clamp(fallingEval, 0.51, 1.51);
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double fallingEval = (1067 + 223 * (mainThread->bestPreviousAverageScore - bestValue)
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+ 97 * (mainThread->iterValue[iterIdx] - bestValue))
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/ 10000.0;
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fallingEval = std::clamp(fallingEval, 0.580, 1.667);
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// If the bestMove is stable over several iterations, reduce time accordingly
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timeReduction = lastBestMoveDepth + 8 < completedDepth ? 1.56 : 0.69;
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double reduction = (1.4 + mainThread->previousTimeReduction) / (2.17 * timeReduction);
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double bestMoveInstability = 1 + 1.79 * totBestMoveChanges / threads.size();
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timeReduction = lastBestMoveDepth + 8 < completedDepth ? 1.495 : 0.687;
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double reduction = (1.48 + mainThread->previousTimeReduction) / (2.17 * timeReduction);
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double bestMoveInstability = 1 + 1.88 * totBestMoveChanges / threads.size();
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double totalTime =
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mainThread->tm.optimum() * fallingEval * reduction * bestMoveInstability;
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@ -446,8 +446,8 @@ void Search::Worker::iterative_deepening() {
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if (rootMoves.size() == 1)
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totalTime = std::min(500.0, totalTime);
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if (completedDepth >= 10 && nodesEffort >= 95
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&& mainThread->tm.elapsed(threads.nodes_searched()) > totalTime * 3 / 4
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if (completedDepth >= 10 && nodesEffort >= 97
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&& mainThread->tm.elapsed(threads.nodes_searched()) > totalTime * 0.739
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&& !mainThread->ponder)
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{
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threads.stop = true;
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@ -464,7 +464,7 @@ void Search::Worker::iterative_deepening() {
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threads.stop = true;
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}
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else if (!mainThread->ponder
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&& mainThread->tm.elapsed(threads.nodes_searched()) > totalTime * 0.50)
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&& mainThread->tm.elapsed(threads.nodes_searched()) > totalTime * 0.506)
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threads.increaseDepth = false;
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else
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threads.increaseDepth = true;
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@ -94,17 +94,17 @@ void TimeManagement::init(Search::LimitsType& limits,
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if (limits.movestogo == 0)
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{
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// Use extra time with larger increments
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double optExtra = limits.inc[us] < 500 ? 1.0 : 1.1;
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double optExtra = limits.inc[us] < 500 ? 1.0 : 1.13;
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// Calculate time constants based on current time left.
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double optConstant =
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std::min(0.00334 + 0.0003 * std::log10(limits.time[us] / 1000.0), 0.0049);
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double maxConstant = std::max(3.4 + 3.0 * std::log10(limits.time[us] / 1000.0), 2.76);
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std::min(0.00308 + 0.000319 * std::log10(limits.time[us] / 1000.0), 0.00506);
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double maxConstant = std::max(3.39 + 3.01 * std::log10(limits.time[us] / 1000.0), 2.93);
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optScale = std::min(0.0120 + std::pow(ply + 3.1, 0.44) * optConstant,
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0.21 * limits.time[us] / double(timeLeft))
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optScale = std::min(0.0122 + std::pow(ply + 2.95, 0.462) * optConstant,
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0.213 * limits.time[us] / double(timeLeft))
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* optExtra;
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maxScale = std::min(6.9, maxConstant + ply / 12.2);
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maxScale = std::min(6.64, maxConstant + ply / 12.0);
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}
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// x moves in y seconds (+ z increment)
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@ -117,7 +117,7 @@ void TimeManagement::init(Search::LimitsType& limits,
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// Limit the maximum possible time for this move
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optimumTime = TimePoint(optScale * timeLeft);
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maximumTime =
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TimePoint(std::min(0.84 * limits.time[us] - moveOverhead, maxScale * optimumTime)) - 10;
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TimePoint(std::min(0.825 * limits.time[us] - moveOverhead, maxScale * optimumTime)) - 10;
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if (options["Ponder"])
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optimumTime += optimumTime / 4;
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