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Tuned nullmove search
Tuning was done with Bayesian optimisation and sequential use of gaussian process regressor and gaussian process classifier. The latter is used in lieu of ordinal categorical modelling. Details will be given in Fishcooking forum topic: https://groups.google.com/forum/?fromgroups=#!topic/fishcooking/b3uhBBJcJG4 STC: LLR: 2.96 (-2.94,2.94) {-1.00,3.00} Total: 10248 W: 2361 L: 2233 D: 5654 Ptnml(0-2): 191, 1153, 2303, 1276, 194 http://tests.stockfishchess.org/tests/view/5e0ba4159d3fbe26f672d4e6 LTC: LLR: 2.94 (-2.94,2.94) {0.00,2.00} Total: 16003 W: 2648 L: 2458 D: 10897 Ptnml(0-2): 121, 1595, 4394, 1718, 153 http://tests.stockfishchess.org/tests/view/5e0bb8519d3fbe26f672d4fd Closes https://github.com/official-stockfish/Stockfish/pull/2468 Bench 4747984
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@ -825,10 +825,10 @@ namespace {
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// Step 9. Null move search with verification search (~40 Elo)
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if ( !PvNode
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&& (ss-1)->currentMove != MOVE_NULL
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&& (ss-1)->statScore < 23405
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&& (ss-1)->statScore < 23397
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&& eval >= beta
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&& eval >= ss->staticEval
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&& ss->staticEval >= beta - 32 * depth + 317 - improving * 30
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&& ss->staticEval >= beta - 32 * depth + 292 - improving * 30
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&& !excludedMove
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&& pos.non_pawn_material(us)
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&& (ss->ply >= thisThread->nmpMinPly || us != thisThread->nmpColor))
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