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[MAX_MOVES]; // [depth or moveNumber]
- template <bool PvNode> Depth reduction(bool i, Depth d, int mn) {
- int r = Reductions[d / ONE_PLY] * Reductions[mn] / 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) {
void Search::init() {
for (int i = 1; i < MAX_MOVES; ++i)
- Reductions[i] = int(1024 * std::log(i) / std::sqrt(1.95));
+ Reductions[i] = int(22.9 * std::log(i));
}
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;
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;
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
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
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
else if (type_of(move) == CASTLING)
extension = ONE_PLY;
+ // Shuffle extension
+ 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;
+
// Passed pawn extension
else if ( move == ss->killers[0]
&& pos.advanced_pawn_push(move)
continue;
// Reduced depth of the next LMR search
- int lmrDepth = std::max(newDepth - reduction<PvNode>(improving, depth, moveCount), DEPTH_ZERO);
+ int lmrDepth = std::max(newDepth - reduction(improving, depth, moveCount), DEPTH_ZERO);
lmrDepth /= ONE_PLY;
// Countermoves based pruning (~20 Elo)
// 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)
{
}
- // 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) {
projects / stockfish / blobdiff