// Different node types, used as a template parameter
enum NodeType { NonPV, PV };
- constexpr uint64_t ttHitAverageWindow = 4096;
- constexpr uint64_t ttHitAverageResolution = 1024;
+ constexpr uint64_t TtHitAverageWindow = 4096;
+ constexpr uint64_t TtHitAverageResolution = 1024;
// Razor and futility margins
- constexpr int RazorMargin = 531;
+ constexpr int RazorMargin = 527;
Value futility_margin(Depth d, bool improving) {
- return Value(217 * (d - improving));
+ return Value(227 * (d - improving));
}
// Reductions lookup table, initialized at startup
Depth reduction(bool i, Depth d, int mn) {
int r = Reductions[d] * Reductions[mn];
- return (r + 511) / 1024 + (!i && r > 1007);
+ return (r + 570) / 1024 + (!i && r > 1018);
}
constexpr int futility_move_count(bool improving, Depth depth) {
- return (4 + depth * depth) / (2 - improving);
+ return (3 + depth * depth) / (2 - improving);
}
// History and stats update bonus, based on depth
int stat_bonus(Depth d) {
- return d > 15 ? -8 : 19 * d * d + 155 * d - 132;
+ return d > 15 ? 27 : 17 * d * d + 133 * d - 134;
}
// Add a small random component to draw evaluations to avoid 3fold-blindness
}
else
{
- for (Thread* th : Threads)
- {
- th->bestMoveChanges = 0;
- if (th != this)
- th->start_searching();
- }
-
- Thread::search(); // Let's start searching!
+ Threads.start_searching(); // start non-main threads
+ Thread::search(); // main thread start searching
}
// When we reach the maximum depth, we can arrive here without a raise of
Threads.stop = true;
// Wait until all threads have finished
- for (Thread* th : Threads)
- if (th != this)
- th->wait_for_search_finished();
+ Threads.wait_for_search_finished();
// When playing in 'nodes as time' mode, subtract the searched nodes from
// the available ones before exiting.
Thread* bestThread = this;
- // Check if there are threads with a better score than main thread
- if ( Options["MultiPV"] == 1
+ if ( int(Options["MultiPV"]) == 1
&& !Limits.depth
- && !(Skill(Options["Skill Level"]).enabled() || Options["UCI_LimitStrength"])
- && rootMoves[0].pv[0] != MOVE_NONE)
- {
- std::map<Move, int64_t> votes;
- Value minScore = this->rootMoves[0].score;
-
- // Find minimum score
- for (Thread* th: Threads)
- minScore = std::min(minScore, th->rootMoves[0].score);
-
- // Vote according to score and depth, and select the best thread
- for (Thread* th : Threads)
- {
- votes[th->rootMoves[0].pv[0]] +=
- (th->rootMoves[0].score - minScore + 14) * int(th->completedDepth);
-
- if (abs(bestThread->rootMoves[0].score) >= VALUE_TB_WIN_IN_MAX_PLY)
- {
- // Make sure we pick the shortest mate / TB conversion or stave off mate the longest
- if (th->rootMoves[0].score > bestThread->rootMoves[0].score)
- bestThread = th;
- }
- else if ( th->rootMoves[0].score >= VALUE_TB_WIN_IN_MAX_PLY
- || ( th->rootMoves[0].score > VALUE_TB_LOSS_IN_MAX_PLY
- && votes[th->rootMoves[0].pv[0]] > votes[bestThread->rootMoves[0].pv[0]]))
- bestThread = th;
- }
- }
+ && !(Skill(Options["Skill Level"]).enabled() || int(Options["UCI_LimitStrength"]))
+ && rootMoves[0].pv[0] != MOVE_NONE)
+ bestThread = Threads.get_best_thread();
bestPreviousScore = bestThread->rootMoves[0].score;
if (mainThread)
{
if (mainThread->bestPreviousScore == VALUE_INFINITE)
- for (int i=0; i<4; ++i)
+ for (int i = 0; i < 4; ++i)
mainThread->iterValue[i] = VALUE_ZERO;
else
- for (int i=0; i<4; ++i)
+ for (int i = 0; i < 4; ++i)
mainThread->iterValue[i] = mainThread->bestPreviousScore;
}
- size_t multiPV = Options["MultiPV"];
+ std::copy(&lowPlyHistory[2][0], &lowPlyHistory.back().back() + 1, &lowPlyHistory[0][0]);
+ std::fill(&lowPlyHistory[MAX_LPH - 2][0], &lowPlyHistory.back().back() + 1, 0);
+
+ size_t multiPV = size_t(Options["MultiPV"]);
// Pick integer skill levels, but non-deterministically round up or down
// such that the average integer skill corresponds to the input floating point one.
multiPV = std::max(multiPV, (size_t)4);
multiPV = std::min(multiPV, rootMoves.size());
- ttHitAverage = ttHitAverageWindow * ttHitAverageResolution / 2;
+ ttHitAverage = TtHitAverageWindow * TtHitAverageResolution / 2;
int ct = int(Options["Contempt"]) * PawnValueEg / 100; // From centipawns
if (rootDepth >= 4)
{
Value prev = rootMoves[pvIdx].previousScore;
- delta = Value(21);
+ delta = Value(19);
alpha = std::max(prev - delta,-VALUE_INFINITE);
beta = std::min(prev + delta, VALUE_INFINITE);
// Adjust contempt based on root move's previousScore (dynamic contempt)
- int dct = ct + (102 - ct / 2) * prev / (abs(prev) + 157);
+ int dct = ct + (110 - ct / 2) * prev / (abs(prev) + 140);
contempt = (us == WHITE ? make_score(dct, dct / 2)
: -make_score(dct, dct / 2));
&& !Threads.stop
&& !mainThread->stopOnPonderhit)
{
- double fallingEval = (332 + 6 * (mainThread->bestPreviousScore - bestValue)
- + 6 * (mainThread->iterValue[iterIdx] - bestValue)) / 704.0;
+ double fallingEval = (296 + 6 * (mainThread->bestPreviousScore - bestValue)
+ + 6 * (mainThread->iterValue[iterIdx] - bestValue)) / 725.0;
fallingEval = Utility::clamp(fallingEval, 0.5, 1.5);
// If the bestMove is stable over several iterations, reduce time accordingly
- timeReduction = lastBestMoveDepth + 9 < completedDepth ? 1.94 : 0.91;
- double reduction = (1.41 + mainThread->previousTimeReduction) / (2.27 * timeReduction);
+ timeReduction = lastBestMoveDepth + 10 < completedDepth ? 1.92 : 0.95;
+ double reduction = (1.47 + mainThread->previousTimeReduction) / (2.22 * timeReduction);
// Use part of the gained time from a previous stable move for the current move
for (Thread* th : Threads)
}
double bestMoveInstability = 1 + totBestMoveChanges / Threads.size();
- // Stop the search if we have only one legal move, or if available time elapsed
- if ( rootMoves.size() == 1
- || Time.elapsed() > Time.optimum() * fallingEval * reduction * bestMoveInstability)
+ double totalTime = rootMoves.size() == 1 ? 0 :
+ Time.optimum() * fallingEval * reduction * bestMoveInstability;
+
+ // Stop the search if we have exceeded the totalTime, at least 1ms search
+ if (Time.elapsed() > totalTime)
{
// If we are allowed to ponder do not stop the search now but
// keep pondering until the GUI sends "ponderhit" or "stop".
}
else if ( Threads.increaseDepth
&& !mainThread->ponder
- && Time.elapsed() > Time.optimum() * fallingEval * reduction * bestMoveInstability * 0.6)
+ && Time.elapsed() > totalTime * 0.56)
Threads.increaseDepth = false;
else
Threads.increaseDepth = true;
Depth extension, newDepth;
Value bestValue, value, ttValue, eval, maxValue;
bool ttHit, ttPv, formerPv, givesCheck, improving, didLMR, priorCapture;
- bool captureOrPromotion, doFullDepthSearch, moveCountPruning, ttCapture, singularLMR;
+ bool captureOrPromotion, doFullDepthSearch, moveCountPruning,
+ ttCapture, singularQuietLMR;
Piece movedPiece;
int moveCount, captureCount, quietCount;
|| pos.is_draw(ss->ply)
|| ss->ply >= MAX_PLY)
return (ss->ply >= MAX_PLY && !ss->inCheck) ? evaluate(pos)
- : value_draw(pos.this_thread());
+ : value_draw(pos.this_thread());
// Step 3. Mate distance pruning. Even if we mate at the next move our score
// would be at best mate_in(ss->ply+1), but if alpha is already bigger because
// search to overwrite a previous full search TT value, so we use a different
// position key in case of an excluded move.
excludedMove = ss->excludedMove;
- posKey = pos.key() ^ Key(excludedMove << 16); // Isn't a very good hash
+ posKey = excludedMove == MOVE_NONE ? pos.key() : pos.key() ^ make_key(excludedMove);
tte = TT.probe(posKey, ttHit);
ttValue = ttHit ? value_from_tt(tte->value(), ss->ply, pos.rule50_count()) : VALUE_NONE;
ttMove = rootNode ? thisThread->rootMoves[thisThread->pvIdx].pv[0]
ttPv = PvNode || (ttHit && tte->is_pv());
formerPv = ttPv && !PvNode;
- if (ttPv && depth > 12 && ss->ply - 1 < MAX_LPH && !pos.captured_piece() && is_ok((ss-1)->currentMove))
+ if ( ttPv
+ && depth > 12
+ && ss->ply - 1 < MAX_LPH
+ && !priorCapture
+ && is_ok((ss-1)->currentMove))
thisThread->lowPlyHistory[ss->ply - 1][from_to((ss-1)->currentMove)] << stat_bonus(depth - 5);
// thisThread->ttHitAverage can be used to approximate the running average of ttHit
- thisThread->ttHitAverage = (ttHitAverageWindow - 1) * thisThread->ttHitAverage / ttHitAverageWindow
- + ttHitAverageResolution * ttHit;
+ thisThread->ttHitAverage = (TtHitAverageWindow - 1) * thisThread->ttHitAverage / TtHitAverageWindow
+ + TtHitAverageResolution * ttHit;
// At non-PV nodes we check for an early TT cutoff
if ( !PvNode
// Step 6. Static evaluation of the position
if (ss->inCheck)
{
+ // Skip early pruning when in check
ss->staticEval = eval = VALUE_NONE;
improving = false;
- goto moves_loop; // Skip early pruning when in check
+ goto moves_loop;
}
else if (ttHit)
{
// Step 9. Null move search with verification search (~40 Elo)
if ( !PvNode
&& (ss-1)->currentMove != MOVE_NULL
- && (ss-1)->statScore < 23397
+ && (ss-1)->statScore < 23824
&& eval >= beta
&& eval >= ss->staticEval
- && ss->staticEval >= beta - 32 * depth - 30 * improving + 120 * ttPv + 292
+ && ss->staticEval >= beta - 33 * depth - 33 * improving + 112 * ttPv + 311
&& !excludedMove
&& pos.non_pawn_material(us)
&& (ss->ply >= thisThread->nmpMinPly || us != thisThread->nmpColor))
assert(eval - beta >= 0);
// Null move dynamic reduction based on depth and value
- Depth R = (854 + 68 * depth) / 258 + std::min(int(eval - beta) / 192, 3);
+ Depth R = (737 + 77 * depth) / 246 + std::min(int(eval - beta) / 192, 3);
ss->currentMove = MOVE_NULL;
ss->continuationHistory = &thisThread->continuationHistory[0][0][NO_PIECE][0];
// If we have a good enough capture and a reduced search returns a value
// much above beta, we can (almost) safely prune the previous move.
if ( !PvNode
- && depth >= 5
+ && depth > 4
&& abs(beta) < VALUE_TB_WIN_IN_MAX_PLY)
{
- Value raisedBeta = beta + 189 - 45 * improving;
+ Value raisedBeta = beta + 176 - 49 * improving;
assert(raisedBeta < VALUE_INFINITE);
MovePicker mp(pos, ttMove, raisedBeta - ss->staticEval, &captureHistory);
int probCutCount = 0;
contHist,
countermove,
ss->killers,
- depth > 12 ? ss->ply : MAX_PLY);
+ ss->ply);
value = bestValue;
- singularLMR = moveCountPruning = false;
+ singularQuietLMR = moveCountPruning = false;
ttCapture = ttMove && pos.capture_or_promotion(ttMove);
// Mark this node as being searched
// Futility pruning: parent node (~5 Elo)
if ( lmrDepth < 6
&& !ss->inCheck
- && ss->staticEval + 235 + 172 * lmrDepth <= alpha
+ && ss->staticEval + 284 + 188 * lmrDepth <= alpha
&& (*contHist[0])[movedPiece][to_sq(move)]
+ (*contHist[1])[movedPiece][to_sq(move)]
- + (*contHist[3])[movedPiece][to_sq(move)] < 27400)
+ + (*contHist[3])[movedPiece][to_sq(move)]
+ + (*contHist[5])[movedPiece][to_sq(move)] / 2 < 28388)
continue;
// Prune moves with negative SEE (~20 Elo)
- if (!pos.see_ge(move, Value(-(32 - std::min(lmrDepth, 18)) * lmrDepth * lmrDepth)))
+ if (!pos.see_ge(move, Value(-(29 - std::min(lmrDepth, 17)) * lmrDepth * lmrDepth)))
continue;
}
else
// Futility pruning for captures
if ( !givesCheck
&& lmrDepth < 6
+ && !(PvNode && abs(bestValue) < 2)
+ && PieceValue[MG][type_of(movedPiece)] >= PieceValue[MG][type_of(pos.piece_on(to_sq(move)))]
&& !ss->inCheck
- && ss->staticEval + 270 + 384 * lmrDepth + PieceValue[MG][type_of(pos.piece_on(to_sq(move)))] <= alpha)
+ && ss->staticEval + 267 + 391 * lmrDepth
+ + PieceValue[MG][type_of(pos.piece_on(to_sq(move)))] <= alpha)
continue;
// See based pruning
- if (!pos.see_ge(move, Value(-194) * depth)) // (~25 Elo)
+ if (!pos.see_ge(move, Value(-202) * depth)) // (~25 Elo)
continue;
}
}
if (value < singularBeta)
{
extension = 1;
- singularLMR = true;
+ singularQuietLMR = !ttCapture;
}
// Multi-cut pruning
else if (singularBeta >= beta)
return singularBeta;
- // If the eval of ttMove is greater than beta we try also if there is an other move that
- // pushes it over beta, if so also produce a cutoff
+ // If the eval of ttMove is greater than beta we try also if there is another
+ // move that pushes it over beta, if so also produce a cutoff.
else if (ttValue >= beta)
{
ss->excludedMove = move;
|| moveCountPruning
|| ss->staticEval + PieceValue[EG][pos.captured_piece()] <= alpha
|| cutNode
- || thisThread->ttHitAverage < 375 * ttHitAverageResolution * ttHitAverageWindow / 1024))
+ || thisThread->ttHitAverage < 415 * TtHitAverageResolution * TtHitAverageWindow / 1024))
{
Depth r = reduction(improving, depth, moveCount);
// Decrease reduction if the ttHit running average is large
- if (thisThread->ttHitAverage > 500 * ttHitAverageResolution * ttHitAverageWindow / 1024)
+ if (thisThread->ttHitAverage > 473 * TtHitAverageResolution * TtHitAverageWindow / 1024)
r--;
- // Reduction if other threads are searching this position.
+ // Reduction if other threads are searching this position
if (th.marked())
r++;
r++;
// Decrease reduction if opponent's move count is high (~5 Elo)
- if ((ss-1)->moveCount > 14)
+ if ((ss-1)->moveCount > 13)
r--;
// Decrease reduction if ttMove has been singularly extended (~3 Elo)
- if (singularLMR)
+ if (singularQuietLMR)
r -= 1 + formerPv;
if (!captureOrPromotion)
// hence break make_move(). (~2 Elo)
else if ( type_of(move) == NORMAL
&& !pos.see_ge(reverse_move(move)))
- r -= 2 + ttPv;
+ r -= 2 + ttPv - (type_of(movedPiece) == PAWN);
ss->statScore = thisThread->mainHistory[us][from_to(move)]
+ (*contHist[0])[movedPiece][to_sq(move)]
+ (*contHist[1])[movedPiece][to_sq(move)]
+ (*contHist[3])[movedPiece][to_sq(move)]
- - 4926;
+ - 4826;
// Decrease/increase reduction by comparing opponent's stat score (~10 Elo)
- if (ss->statScore >= -102 && (ss-1)->statScore < -114)
+ if (ss->statScore >= -100 && (ss-1)->statScore < -112)
r--;
- else if ((ss-1)->statScore >= -116 && ss->statScore < -154)
+ else if ((ss-1)->statScore >= -125 && ss->statScore < -138)
r++;
// Decrease/increase reduction for moves with a good/bad history (~30 Elo)
- r -= ss->statScore / 16434;
+ r -= ss->statScore / 14615;
}
else
{
// Unless giving check, this capture is likely bad
if ( !givesCheck
- && ss->staticEval + PieceValue[EG][pos.captured_piece()] + 200 * depth <= alpha)
+ && ss->staticEval + PieceValue[EG][pos.captured_piece()] + 211 * depth <= alpha)
r++;
}
rm.pv.push_back(*m);
// We record how often the best move has been changed in each
- // iteration. This information is used for time management: When
+ // iteration. This information is used for time management: when
// the best move changes frequently, we allocate some more time.
if (moveCount > 1)
++thisThread->bestMoveChanges;
if (PvNode && bestValue > alpha)
alpha = bestValue;
- futilityBase = bestValue + 154;
+ futilityBase = bestValue + 141;
}
const PieceToHistory* contHist[] = { (ss-1)->continuationHistory, (ss-2)->continuationHistory,
// Initialize a MovePicker object for the current position, and prepare
// to search the moves. Because the depth is <= 0 here, only captures,
- // queen promotions and checks (only if depth >= DEPTH_QS_CHECKS) will
- // be generated.
+ // queen and checking knight promotions, and other checks(only if depth >= DEPTH_QS_CHECKS)
+ // will be generated.
MovePicker mp(pos, ttMove, depth, &thisThread->mainHistory,
&thisThread->captureHistory,
contHist,
}
}
- // Don't search moves with negative SEE values
+ // Do not search moves with negative SEE values
if ( !ss->inCheck && !pos.see_ge(move))
continue;
}
}
- // All legal moves have been searched. A special case: If we're in check
+ // All legal moves have been searched. A special case: if we're in check
// and no legal moves were found, it is checkmate.
if (ss->inCheck && bestValue == -VALUE_INFINITE)
return mated_in(ss->ply); // Plies to mate from the root
// value_to_tt() adjusts a mate or TB score from "plies to mate from the root" to
- // "plies to mate from the current position". standard scores are unchanged.
+ // "plies to mate from the current position". Standard scores are unchanged.
// The function is called before storing a value in the transposition table.
Value value_to_tt(Value v, int ply) {
}
- // value_from_tt() is the inverse of value_to_tt(): It adjusts a mate or TB score
- // from the transposition table (which refers to the plies to mate/be mated
- // from current position) to "plies to mate/be mated (TB win/loss) from the root".
- // However, for mate scores, to avoid potentially false mate scores related to the 50 moves rule,
- // and the graph history interaction, return an optimal TB score instead.
+ // value_from_tt() is the inverse of value_to_tt(): it adjusts a mate or TB score
+ // from the transposition table (which refers to the plies to mate/be mated from
+ // current position) to "plies to mate/be mated (TB win/loss) from the root". However,
+ // for mate scores, to avoid potentially false mate scores related to the 50 moves rule
+ // and the graph history interaction, we return an optimal TB score instead.
Value value_from_tt(Value v, int ply, int r50c) {
thisThread->counterMoves[pos.piece_on(prevSq)][prevSq] = move;
}
- if (depth > 12 && ss->ply < MAX_LPH)
- thisThread->lowPlyHistory[ss->ply][from_to(move)] << stat_bonus(depth - 7);
+ if (depth > 11 && ss->ply < MAX_LPH)
+ thisThread->lowPlyHistory[ss->ply][from_to(move)] << stat_bonus(depth - 6);
}
// When playing with strength handicap, choose best move among a set of RootMoves
} // namespace
+
/// MainThread::check_time() is used to print debug info and, more importantly,
/// to detect when we are out of available time and thus stop the search.
<< " multipv " << i + 1
<< " score " << UCI::value(v);
+ if (Options["UCI_ShowWDL"])
+ ss << UCI::wdl(v, pos.game_ply());
+
if (!tb && i == pvIdx)
ss << (v >= beta ? " lowerbound" : v <= alpha ? " upperbound" : "");
projects / stockfish / blobdiff