const bool Slidings[18] = { 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1 };
inline bool piece_is_slider(Piece p) { return Slidings[p]; }
- // Step 6. Razoring
-
// Maximum depth for razoring
const Depth RazorDepth = 4 * ONE_PLY;
// Maximum depth for use of dynamic threat detection when null move fails low
const Depth ThreatDepth = 5 * ONE_PLY;
- // Step 9. Internal iterative deepening
-
// Minimum depth for use of internal iterative deepening
const Depth IIDDepth[] = { 8 * ONE_PLY, 5 * ONE_PLY };
// when the static evaluation is bigger then beta - IIDMargin.
const Value IIDMargin = Value(0x100);
- // Step 11. Decide the new search depth
-
- // Extensions. Array index 0 is used for non-PV nodes, index 1 for PV nodes
- const Depth CheckExtension[] = { ONE_PLY / 2, ONE_PLY / 1 };
- const Depth PawnEndgameExtension[] = { ONE_PLY / 1, ONE_PLY / 1 };
- const Depth PawnPushTo7thExtension[] = { ONE_PLY / 2, ONE_PLY / 2 };
- const Depth PassedPawnExtension[] = { DEPTH_ZERO, ONE_PLY / 2 };
-
// Minimum depth for use of singular extension
const Depth SingularExtensionDepth[] = { 8 * ONE_PLY, 6 * ONE_PLY };
- // Step 12. Futility pruning
-
// Futility margin for quiescence search
const Value FutilityMarginQS = Value(0x80);
return d < 16 * ONE_PLY ? FutilityMoveCounts[d] : MAX_MOVES;
}
- // Step 14. Reduced search
-
// Reduction lookup tables (initialized at startup) and their access function
int8_t Reductions[2][64][64]; // [pv][depth][moveNumber]
RootMoveList Rml;
// MultiPV mode
- int MultiPV, UCIMultiPV, MultiPVIdx;
+ size_t MultiPV, UCIMultiPV, MultiPVIdx;
// Time management variables
TimeManager TimeMgr;
return os;
}
- // extension() decides whether a move should be searched with normal depth,
- // or with extended depth. Certain classes of moves (checking moves, in
- // particular) are searched with bigger depth than ordinary moves and in
- // any case are marked as 'dangerous'. Note that also if a move is not
- // extended, as example because the corresponding UCI option is set to zero,
- // the move is marked as 'dangerous' so, at least, we avoid to prune it.
- template <bool PvNode>
- FORCE_INLINE Depth extension(const Position& pos, Move m, bool captureOrPromotion,
- bool moveIsCheck, bool* dangerous) {
- assert(m != MOVE_NONE);
-
- Depth result = DEPTH_ZERO;
- *dangerous = moveIsCheck;
-
- if (moveIsCheck && pos.see_sign(m) >= 0)
- result += CheckExtension[PvNode];
+ // is_dangerous() checks whether a move belongs to some classes of known
+ // 'dangerous' moves so that we avoid to prune it.
+ FORCE_INLINE bool is_dangerous(const Position& pos, Move m, bool captureOrPromotion) {
+ // Test for a pawn pushed to 7th or a passed pawn move
if (type_of(pos.piece_on(move_from(m))) == PAWN)
{
Color c = pos.side_to_move();
- if (relative_rank(c, move_to(m)) == RANK_7)
- {
- result += PawnPushTo7thExtension[PvNode];
- *dangerous = true;
- }
- if (pos.pawn_is_passed(c, move_to(m)))
- {
- result += PassedPawnExtension[PvNode];
- *dangerous = true;
- }
+ if ( relative_rank(c, move_to(m)) == RANK_7
+ || pos.pawn_is_passed(c, move_to(m)))
+ return true;
}
+ // Test for a capture that triggers a pawn endgame
if ( captureOrPromotion
&& type_of(pos.piece_on(move_to(m))) != PAWN
&& ( pos.non_pawn_material(WHITE) + pos.non_pawn_material(BLACK)
- PieceValueMidgame[pos.piece_on(move_to(m))] == VALUE_ZERO)
&& !is_special(m))
- {
- result += PawnEndgameExtension[PvNode];
- *dangerous = true;
- }
+ return true;
- return std::min(result, ONE_PLY);
+ return false;
}
} // namespace
TT.clear();
}
- UCIMultiPV = Options["MultiPV"].value<int>();
- SkillLevel = Options["Skill Level"].value<int>();
+ UCIMultiPV = Options["MultiPV"].value<size_t>();
+ SkillLevel = Options["Skill Level"].value<size_t>();
// Do we have to play with skill handicap? In this case enable MultiPV that
// we will use behind the scenes to retrieve a set of possible moves.
SkillLevelEnabled = (SkillLevel < 20);
- MultiPV = (SkillLevelEnabled ? std::max(UCIMultiPV, 4) : UCIMultiPV);
+ MultiPV = (SkillLevelEnabled ? std::max(UCIMultiPV, (size_t)4) : UCIMultiPV);
// Write current search header to log file
if (Options["Use Search Log"].value<bool>())
Rml.init(pos, rootMoves);
// Handle special case of searching on a mate/stalemate position
- if (!Rml.size())
+ if (Rml.empty())
{
cout << "info" << depth_to_uci(DEPTH_ZERO)
<< score_to_uci(pos.in_check() ? -VALUE_MATE : VALUE_DRAW, alpha, beta) << endl;
Rml.bestMoveChanges = 0;
// MultiPV loop. We perform a full root search for each PV line
- for (MultiPVIdx = 0; MultiPVIdx < std::min(MultiPV, (int)Rml.size()); MultiPVIdx++)
+ for (MultiPVIdx = 0; MultiPVIdx < std::min(MultiPV, Rml.size()); MultiPVIdx++)
{
// Calculate dynamic aspiration window based on previous iterations
if (depth >= 5 && abs(Rml[MultiPVIdx].prevScore) < VALUE_KNOWN_WIN)
// Write PV back to transposition table in case the relevant entries
// have been overwritten during the search.
- for (int i = 0; i <= MultiPVIdx; i++)
+ for (size_t i = 0; i <= MultiPVIdx; i++)
Rml[i].insert_pv_in_tt(pos);
// If search has been stopped exit the aspiration window loop,
// protocol requires to send all the PV lines also if are still
// to be searched and so refer to the previous search's score.
if ((bestValue > alpha && bestValue < beta) || elapsed_time() > 2000)
- for (int i = 0; i < std::min(UCIMultiPV, (int)Rml.size()); i++)
+ for (size_t i = 0; i < std::min(UCIMultiPV, Rml.size()); i++)
{
bool updated = (i <= MultiPVIdx);
{
lock_grab(&(sp->lock));
bestValue = sp->bestValue;
+ moveCount = sp->moveCount;
+
+ assert(bestValue > -VALUE_INFINITE && moveCount > 0);
}
// Step 11. Loop through moves
}
isPvMove = (PvNode && moveCount <= 1);
- givesCheck = pos.move_gives_check(move, ci);
captureOrPromotion = pos.is_capture_or_promotion(move);
+ givesCheck = pos.move_gives_check(move, ci);
+ dangerous = givesCheck || is_dangerous(pos, move, captureOrPromotion);
+ ext = DEPTH_ZERO;
- // Step 12. Decide the new search depth
- ext = extension<PvNode>(pos, move, captureOrPromotion, givesCheck, &dangerous);
+ // Step 12. Extend checks and, in PV nodes, also dangerous moves
+ if (PvNode && dangerous)
+ ext = ONE_PLY;
+
+ else if (givesCheck && pos.see_sign(move) >= 0)
+ ext = PvNode ? ONE_PLY : ONE_PLY / 2;
// Singular extension search. If all moves but one fail low on a search of
// (alpha-s, beta-s), and just one fails high on (alpha, beta), then that move
// on all the other moves but the ttMove, if result is lower than ttValue minus
// a margin then we extend ttMove.
if ( singularExtensionNode
+ && !ext
&& move == ttMove
- && pos.pl_move_is_legal(move, ci.pinned)
- && ext < ONE_PLY)
+ && pos.pl_move_is_legal(move, ci.pinned))
{
Value ttValue = value_from_tt(tte->value(), ss->ply);
if (futilityValue < beta)
{
if (SpNode)
- {
lock_grab(&(sp->lock));
- if (futilityValue > sp->bestValue)
- sp->bestValue = bestValue = futilityValue;
- }
- else if (futilityValue > bestValue)
- bestValue = futilityValue;
continue;
}
// case of StopRequest or thread.cutoff_occurred() are set, but this is
// harmless because return value is discarded anyhow in the parent nodes.
// If we are in a singular extension search then return a fail low score.
- if (!SpNode && !moveCount)
+ if (!moveCount)
return excludedMove ? oldAlpha : inCheck ? value_mated_in(ss->ply) : VALUE_DRAW;
+ // We have pruned all the moves, so return a fail-low score
+ if (bestValue == -VALUE_INFINITE)
+ {
+ assert(!playedMoveCount);
+
+ bestValue = alpha;
+ }
+
// Step 21. Update tables
// If the search is not aborted, update the transposition table,
// history counters, and killer moves.
// Rml list is already sorted by score in descending order
int s;
+ size_t size = std::min(MultiPV, Rml.size());
int max_s = -VALUE_INFINITE;
- int size = std::min(MultiPV, (int)Rml.size());
int max = Rml[0].score;
int var = std::min(max - Rml[size - 1].score, int(PawnValueMidgame));
int wk = 120 - 2 * SkillLevel;
// Choose best move. For each move's score we add two terms both dependent
// on wk, one deterministic and bigger for weaker moves, and one random,
// then we choose the move with the resulting highest score.
- for (int i = 0; i < size; i++)
+ for (size_t i = 0; i < size; i++)
{
s = Rml[i].score;