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doEvenDeeperSearch + tuning

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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
This commit is contained in:
FauziAkram 2022-12-02 18:23:28 +03:00 • committed by Joost VandeVondele
parent 9fc203a3d0
commit 98965c139d
2 changed files with 11 additions and 10 deletions
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14
src/evaluate.cpp
View file

@ -1063,7 +1063,7 @@ Value Eval::evaluate(const Position& pos, int* complexity) {
else else
{ {
int nnueComplexity; int nnueComplexity;
int scale = 1064 + 106 * pos.non_pawn_material() / 5120; int scale = 1076 + 96 * pos.non_pawn_material() / 5120;
Color stm = pos.side_to_move(); Color stm = pos.side_to_move();
Value optimism = pos.this_thread()->optimism[stm]; Value optimism = pos.this_thread()->optimism[stm];
@ -1071,21 +1071,21 @@ Value Eval::evaluate(const Position& pos, int* complexity) {
Value nnue = NNUE::evaluate(pos, true, &nnueComplexity); Value nnue = NNUE::evaluate(pos, true, &nnueComplexity);
// Blend nnue complexity with (semi)classical complexity // Blend nnue complexity with (semi)classical complexity
nnueComplexity = ( 416 * nnueComplexity nnueComplexity = ( 412 * nnueComplexity
+ 424 * abs(psq - nnue) + 428 * abs(psq - nnue)
+ (optimism > 0 ? int(optimism) * int(psq - nnue) : 0) + (optimism > 0 ? int(optimism) * int(psq - nnue) : 0)
) / 1024; ) / 1026;
// Return hybrid NNUE complexity to caller // Return hybrid NNUE complexity to caller
if (complexity) if (complexity)
*complexity = nnueComplexity; *complexity = nnueComplexity;
optimism = optimism * (269 + nnueComplexity) / 256; optimism = optimism * (278 + nnueComplexity) / 256;
v = (nnue * scale + optimism * (scale - 754)) / 1024; v = (nnue * scale + optimism * (scale - 755)) / 1024;
} }
// Damp down the evaluation linearly when shuffling // Damp down the evaluation linearly when shuffling
v = v * (195 - pos.rule50_count()) / 211; v = v * (197 - pos.rule50_count()) / 214;
// Guarantee evaluation does not hit the tablebase range // 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); v = std::clamp(v, VALUE_TB_LOSS_IN_MAX_PLY + 1, VALUE_TB_WIN_IN_MAX_PLY - 1);

7
src/search.cpp
View file

@ -81,7 +81,7 @@ namespace {
// History and stats update bonus, based on depth // History and stats update bonus, based on depth
int stat_bonus(Depth d) { int stat_bonus(Depth d) {
return std::min((12 * d + 282) * d - 349 , 1594); return std::min((12 * d + 282) * d - 349 , 1480);
} }
// Add a small random component to draw evaluations to avoid 3-fold blindness // Add a small random component to draw evaluations to avoid 3-fold blindness
@ -1172,7 +1172,7 @@ moves_loop: // When in check, search starts here
- 4433; - 4433;
// Decrease/increase reduction for moves with a good/bad history (~30 Elo) // Decrease/increase reduction for moves with a good/bad history (~30 Elo)
r -= ss->statScore / (13628 + 4000 * (depth > 7 && depth < 19)); r -= ss->statScore / (13000 + 4152 * (depth > 7 && depth < 19));
// In general we want to cap the LMR depth search at newDepth, but when // In general we want to cap the LMR depth search at newDepth, but when
// reduction is negative, we allow this move a limited search extension // reduction is negative, we allow this move a limited search extension
@ -1187,9 +1187,10 @@ moves_loop: // When in check, search starts here
// Adjust full depth search based on LMR results - if result // Adjust full depth search based on LMR results - if result
// was good enough search deeper, if it was bad enough search shallower // was good enough search deeper, if it was bad enough search shallower
const bool doDeeperSearch = value > (alpha + 64 + 11 * (newDepth - d)); const bool doDeeperSearch = value > (alpha + 64 + 11 * (newDepth - d));
const bool doEvenDeeperSearch = value > alpha + 582;
const bool doShallowerSearch = value < bestValue + newDepth; const bool doShallowerSearch = value < bestValue + newDepth;
newDepth += doDeeperSearch - doShallowerSearch; newDepth += doDeeperSearch - doShallowerSearch + doEvenDeeperSearch;
if (newDepth > d) if (newDepth > d)
value = -search<NonPV>(pos, ss+1, -(alpha+1), -alpha, newDepth, !cutNode); value = -search<NonPV>(pos, ss+1, -(alpha+1), -alpha, newDepth, !cutNode);