along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
+#include <algorithm>
#include <cassert>
#include <cmath>
#include <cstring> // For std::memset
}
// Reductions lookup table, initialized at startup
- int Reductions[64]; // [depth or moveNumber]
+ int Reductions[MAX_MOVES]; // [depth or moveNumber]
- template <bool PvNode> Depth reduction(bool i, Depth d, int mn) {
- int r = Reductions[std::min(d / ONE_PLY, 63)] * Reductions[std::min(mn, 63)] / 1024;
- return ((r + 512) / 1024 + (!i && r > 1024) - PvNode) * ONE_PLY;
+ Depth reduction(bool i, Depth d, int mn) {
+ int r = Reductions[d / ONE_PLY] * Reductions[mn];
+ return ((r + 512) / 1024 + (!i && r > 1024)) * ONE_PLY;
}
constexpr int futility_move_count(bool improving, int depth) {
// Add a small random component to draw evaluations to avoid 3fold-blindness
Value value_draw(Depth depth, Thread* thisThread) {
- return depth < 4 ? VALUE_DRAW
- : VALUE_DRAW + Value(2 * (thisThread->nodes & 1) - 1);
+ return depth < 4 * ONE_PLY ? VALUE_DRAW
+ : VALUE_DRAW + Value(2 * (thisThread->nodes & 1) - 1);
}
// Skill structure is used to implement strength limit
void Search::init() {
- for (int i = 1; i < 64; ++i)
- Reductions[i] = int(1024 * std::log(i) / std::sqrt(1.95));
+ for (int i = 1; i < MAX_MOVES; ++i)
+ Reductions[i] = int(22.9 * std::log(i));
}
else
{
for (Thread* th : Threads)
+ {
+ th->bestMoveChanges = 0;
if (th != this)
th->start_searching();
+ }
Thread::search(); // Let's start searching!
}
for (Thread* th: Threads)
minScore = std::min(minScore, th->rootMoves[0].score);
- // Vote according to score and depth
+ // Vote according to score and depth, and select the best thread
+ int64_t bestVote = 0;
for (Thread* th : Threads)
{
- int64_t s = th->rootMoves[0].score - minScore + 1;
- votes[th->rootMoves[0].pv[0]] += 200 + s * s * int(th->completedDepth);
- }
+ votes[th->rootMoves[0].pv[0]] +=
+ (th->rootMoves[0].score - minScore + 14) * int(th->completedDepth);
- // Select best thread
- auto bestVote = votes[this->rootMoves[0].pv[0]];
- for (Thread* th : Threads)
if (votes[th->rootMoves[0].pv[0]] > bestVote)
{
bestVote = votes[th->rootMoves[0].pv[0]];
bestThread = th;
}
+ }
}
previousScore = bestThread->rootMoves[0].score;
Move lastBestMove = MOVE_NONE;
Depth lastBestMoveDepth = DEPTH_ZERO;
MainThread* mainThread = (this == Threads.main() ? Threads.main() : nullptr);
- double timeReduction = 1.0;
+ double timeReduction = 1, totBestMoveChanges = 0;
Color us = rootPos.side_to_move();
std::memset(ss-7, 0, 10 * sizeof(Stack));
bestValue = delta = alpha = -VALUE_INFINITE;
beta = VALUE_INFINITE;
- if (mainThread)
- mainThread->bestMoveChanges = 0;
-
size_t multiPV = Options["MultiPV"];
Skill skill(Options["Skill Level"]);
{
// Age out PV variability metric
if (mainThread)
- mainThread->bestMoveChanges *= 0.517;
+ totBestMoveChanges /= 2;
// Save the last iteration's scores before first PV line is searched and
// all the move scores except the (new) PV are set to -VALUE_INFINITE.
beta = (alpha + beta) / 2;
alpha = std::max(bestValue - delta, -VALUE_INFINITE);
+ failedHighCnt = 0;
if (mainThread)
- {
- failedHighCnt = 0;
mainThread->stopOnPonderhit = false;
- }
}
else if (bestValue >= beta)
{
beta = std::min(bestValue + delta, VALUE_INFINITE);
- if (mainThread)
- ++failedHighCnt;
+ ++failedHighCnt;
}
else
break;
&& !Threads.stop
&& !mainThread->stopOnPonderhit)
{
- double fallingEval = (306 + 9 * (mainThread->previousScore - bestValue)) / 581.0;
+ double fallingEval = (314 + 9 * (mainThread->previousScore - bestValue)) / 581.0;
fallingEval = clamp(fallingEval, 0.5, 1.5);
// If the bestMove is stable over several iterations, reduce time accordingly
double reduction = std::pow(mainThread->previousTimeReduction, 0.528) / timeReduction;
// Use part of the gained time from a previous stable move for the current move
- double bestMoveInstability = 1.0 + mainThread->bestMoveChanges;
+ for (Thread* th : Threads)
+ {
+ totBestMoveChanges += th->bestMoveChanges;
+ th->bestMoveChanges = 0;
+ }
+ 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
Key posKey;
Move ttMove, move, excludedMove, bestMove;
Depth extension, newDepth;
- Value bestValue, value, ttValue, eval, maxValue, pureStaticEval;
+ Value bestValue, value, ttValue, eval, maxValue;
bool ttHit, ttPv, inCheck, givesCheck, improving;
bool captureOrPromotion, doFullDepthSearch, moveCountPruning, ttCapture;
Piece movedPiece;
assert(0 <= ss->ply && ss->ply < MAX_PLY);
(ss+1)->ply = ss->ply + 1;
- ss->currentMove = (ss+1)->excludedMove = bestMove = MOVE_NONE;
- ss->continuationHistory = &thisThread->continuationHistory[NO_PIECE][0];
+ (ss+1)->excludedMove = bestMove = MOVE_NONE;
(ss+2)->killers[0] = (ss+2)->killers[1] = MOVE_NONE;
Square prevSq = to_sq((ss-1)->currentMove);
// starts with statScore = 0. Later grandchildren start with the last calculated
// statScore of the previous grandchild. This influences the reduction rules in
// LMR which are based on the statScore of parent position.
- (ss+2)->statScore = 0;
+ if (rootNode)
+ (ss + 4)->statScore = 0;
+ else
+ (ss + 2)->statScore = 0;
// Step 4. Transposition table lookup. We don't want the score of a partial
// search to overwrite a previous full search TT value, so we use a different
: ttHit ? tte->move() : MOVE_NONE;
ttPv = (ttHit && tte->is_pv()) || (PvNode && depth > 4 * ONE_PLY);
- // if position has been searched at higher depths and we are shuffling, return value_draw
- if (pos.rule50_count() > 36
- && ss->ply > 36
- && depth < 3 * ONE_PLY
- && ttHit
- && tte->depth() > depth
- && pos.count<PAWN>() > 0)
- return VALUE_DRAW;
-
// At non-PV nodes we check for an early TT cutoff
if ( !PvNode
&& ttHit
if (!pos.capture_or_promotion(ttMove))
update_quiet_stats(pos, ss, ttMove, nullptr, 0, stat_bonus(depth));
- // Extra penalty for a quiet TT or main killer move in previous ply when it gets refuted
- if ( ((ss-1)->moveCount == 1 || (ss-1)->currentMove == (ss-1)->killers[0])
- && !pos.captured_piece())
+ // Extra penalty for early quiet moves of the previous ply
+ if ((ss-1)->moveCount <= 2 && !pos.captured_piece())
update_continuation_histories(ss-1, pos.piece_on(prevSq), prevSq, -stat_bonus(depth + ONE_PLY));
}
// Penalty for a quiet ttMove that fails low
// Step 6. Static evaluation of the position
if (inCheck)
{
- ss->staticEval = eval = pureStaticEval = VALUE_NONE;
+ ss->staticEval = eval = VALUE_NONE;
improving = false;
goto moves_loop; // Skip early pruning when in check
}
else if (ttHit)
{
// Never assume anything on values stored in TT
- ss->staticEval = eval = pureStaticEval = tte->eval();
+ ss->staticEval = eval = tte->eval();
if (eval == VALUE_NONE)
- ss->staticEval = eval = pureStaticEval = evaluate(pos);
+ ss->staticEval = eval = evaluate(pos);
// Can ttValue be used as a better position evaluation?
if ( ttValue != VALUE_NONE
{
int bonus = -(ss-1)->statScore / 512;
- pureStaticEval = evaluate(pos);
- ss->staticEval = eval = pureStaticEval + bonus;
+ ss->staticEval = eval = evaluate(pos) + bonus;
}
else
- ss->staticEval = eval = pureStaticEval = -(ss-1)->staticEval + 2 * Eval::Tempo;
+ ss->staticEval = eval = -(ss-1)->staticEval + 2 * Eval::Tempo;
- tte->save(posKey, VALUE_NONE, ttPv, BOUND_NONE, DEPTH_NONE, MOVE_NONE, pureStaticEval);
+ tte->save(posKey, VALUE_NONE, ttPv, BOUND_NONE, DEPTH_NONE, MOVE_NONE, eval);
}
// Step 7. Razoring (~2 Elo)
&& (ss-1)->currentMove != MOVE_NULL
&& (ss-1)->statScore < 23200
&& eval >= beta
- && pureStaticEval >= beta - 36 * depth / ONE_PLY + 225
+ && ss->staticEval >= beta - 36 * depth / ONE_PLY + 225
&& !excludedMove
&& pos.non_pawn_material(us)
&& (ss->ply >= thisThread->nmpMinPly || us != thisThread->nmpColor))
// Do verification search at high depths, with null move pruning disabled
// for us, until ply exceeds nmpMinPly.
- thisThread->nmpMinPly = ss->ply + 3 * (depth-R) / 4;
+ thisThread->nmpMinPly = ss->ply + 3 * (depth-R) / (4 * ONE_PLY);
thisThread->nmpColor = us;
Value v = search<NonPV>(pos, ss, beta-1, beta, depth-R, false);
value = bestValue; // Workaround a bogus 'uninitialized' warning under gcc
moveCountPruning = false;
ttCapture = ttMove && pos.capture_or_promotion(ttMove);
+ int singularExtensionLMRmultiplier = 0;
// Step 12. Loop through all pseudo-legal moves until no moves remain
// or a beta cutoff occurs.
&& move == ttMove
&& !rootNode
&& !excludedMove // Avoid recursive singular search
- /* && ttValue != VALUE_NONE Already implicit in the next condition */
+ /* && ttValue != VALUE_NONE Already implicit in the next condition */
&& abs(ttValue) < VALUE_KNOWN_WIN
&& (tte->bound() & BOUND_LOWER)
&& tte->depth() >= depth - 3 * ONE_PLY
&& pos.legal(move))
{
Value singularBeta = ttValue - 2 * depth / ONE_PLY;
+ Depth halfDepth = depth / (2 * ONE_PLY) * ONE_PLY; // ONE_PLY invariant
ss->excludedMove = move;
- value = search<NonPV>(pos, ss, singularBeta - 1, singularBeta, depth / 2, cutNode);
+ value = search<NonPV>(pos, ss, singularBeta - 1, singularBeta, halfDepth, cutNode);
ss->excludedMove = MOVE_NONE;
if (value < singularBeta)
+ {
extension = ONE_PLY;
+ singularExtensionLMRmultiplier++;
+ if (value < singularBeta - std::min(3 * depth / ONE_PLY, 39))
+ singularExtensionLMRmultiplier++;
+ }
// Multi-cut pruning
// Our ttMove is assumed to fail high, and now we failed high also on a reduced
&& (pos.blockers_for_king(~us) & from_sq(move) || pos.see_ge(move)))
extension = ONE_PLY;
+ // Castling extension
+ else if (type_of(move) == CASTLING)
+ extension = ONE_PLY;
+
// Shuffle extension
- else if(pos.rule50_count() > 14 && ss->ply > 14 && depth < 3 * ONE_PLY && PvNode)
+ else if ( PvNode
+ && pos.rule50_count() > 18
+ && depth < 3 * ONE_PLY
+ && ss->ply < 3 * thisThread->rootDepth / ONE_PLY) // To avoid too deep searches
extension = ONE_PLY;
- // Castling extension
- else if (type_of(move) == CASTLING)
+ // Passed pawn extension
+ else if ( move == ss->killers[0]
+ && pos.advanced_pawn_push(move)
+ && pos.pawn_passed(us, to_sq(move)))
extension = ONE_PLY;
// Calculate new depth for this move
continue;
// Reduced depth of the next LMR search
- int lmrDepth = std::max(newDepth - reduction<PvNode>(improving, depth, moveCount), DEPTH_ZERO) / ONE_PLY;
+ int lmrDepth = std::max(newDepth - reduction(improving, depth, moveCount), DEPTH_ZERO);
+ lmrDepth /= ONE_PLY;
// Countermoves based pruning (~20 Elo)
if ( lmrDepth < 3 + ((ss-1)->statScore > 0 || (ss-1)->moveCount == 1)
// Step 16. Reduced depth search (LMR). If the move fails high it will be
// re-searched at full depth.
if ( depth >= 3 * ONE_PLY
- && moveCount > 1
- && (!captureOrPromotion || moveCountPruning))
+ && moveCount > 1 + 3 * rootNode
+ && ( !captureOrPromotion
+ || moveCountPruning
+ || ss->staticEval + PieceValue[EG][pos.captured_piece()] <= alpha))
{
- Depth r = reduction<PvNode>(improving, depth, moveCount);
+ Depth r = reduction(improving, depth, moveCount);
// Decrease reduction if position is or has been on the PV
if (ttPv)
- r -= ONE_PLY;
+ r -= 2 * ONE_PLY;
// Decrease reduction if opponent's move count is high (~10 Elo)
if ((ss-1)->moveCount > 15)
r -= ONE_PLY;
+ // Decrease reduction if move has been singularly extended
+ r -= singularExtensionLMRmultiplier * ONE_PLY;
if (!captureOrPromotion)
{
// We record how often the best move has been changed in each
// iteration. This information is used for time management: When
// the best move changes frequently, we allocate some more time.
- if (moveCount > 1 && thisThread == Threads.main())
- ++static_cast<MainThread*>(thisThread)->bestMoveChanges;
+ if (moveCount > 1)
+ ++thisThread->bestMoveChanges;
}
else
// All other moves but the PV are set to the lowest value: this
tte->save(posKey, value_to_tt(bestValue, ss->ply), ttPv,
bestValue >= beta ? BOUND_LOWER :
PvNode && bestMove ? BOUND_EXACT : BOUND_UPPER,
- depth, bestMove, pureStaticEval);
+ depth, bestMove, ss->staticEval);
assert(bestValue > -VALUE_INFINITE && bestValue < VALUE_INFINITE);
}
- // qsearch() is the quiescence search function, which is called by the main
- // search function with depth zero, or recursively with depth less than ONE_PLY.
+ // qsearch() is the quiescence search function, which is called by the main search
+ // function with zero depth, or recursively with further decreasing depth per call.
template <NodeType NT>
Value qsearch(Position& pos, Stack* ss, Value alpha, Value beta, Depth depth) {
Thread* thisThread = pos.this_thread();
(ss+1)->ply = ss->ply + 1;
- ss->currentMove = bestMove = MOVE_NONE;
- ss->continuationHistory = &thisThread->continuationHistory[NO_PIECE][0];
+ bestMove = MOVE_NONE;
inCheck = pos.checkers();
moveCount = 0;
projects / stockfish / blobdiff