/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
- Copyright (C) 2004-2021 The Stockfish developers (see AUTHORS file)
+ Copyright (C) 2004-2022 The Stockfish developers (see AUTHORS file)
Stockfish is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
namespace {
// Different node types, used as a template parameter
- enum NodeType { NonPV, PV };
-
- constexpr uint64_t TtHitAverageWindow = 4096;
- constexpr uint64_t TtHitAverageResolution = 1024;
+ enum NodeType { NonPV, PV, Root };
// Futility margin
Value futility_margin(Depth d, bool improving) {
- return Value(234 * (d - improving));
+ return Value(214 * (d - improving));
}
// Reductions lookup table, initialized at startup
int Reductions[MAX_MOVES]; // [depth or moveNumber]
- Depth reduction(bool i, Depth d, int mn) {
+ Depth reduction(bool i, Depth d, int mn, Value delta, Value rootDelta) {
int r = Reductions[d] * Reductions[mn];
- return (r + 503) / 1024 + (!i && r > 915);
+ return (r + 1358 - int(delta) * 1024 / int(rootDelta)) / 1024 + (!i && r > 904);
}
constexpr int futility_move_count(bool improving, Depth depth) {
// History and stats update bonus, based on depth
int stat_bonus(Depth d) {
- return d > 14 ? 66 : 6 * d * d + 231 * d - 206;
+ return std::min((6 * d + 229) * d - 215 , 2000);
}
// Add a small random component to draw evaluations to avoid 3-fold blindness
return VALUE_DRAW + Value(2 * (thisThread->nodes & 1) - 1);
}
- // Skill structure is used to implement strength limit
+ // Check if the current thread is in a search explosion
+ ExplosionState search_explosion(Thread* thisThread) {
+
+ uint64_t nodesNow = thisThread->nodes;
+ bool explosive = thisThread->doubleExtensionAverage[WHITE].is_greater(2, 100)
+ || thisThread->doubleExtensionAverage[BLACK].is_greater(2, 100);
+
+ if (explosive)
+ thisThread->nodesLastExplosive = nodesNow;
+ else
+ thisThread->nodesLastNormal = nodesNow;
+
+ if ( explosive
+ && thisThread->state == EXPLOSION_NONE
+ && nodesNow - thisThread->nodesLastNormal > 6000000)
+ thisThread->state = MUST_CALM_DOWN;
+
+ if ( thisThread->state == MUST_CALM_DOWN
+ && nodesNow - thisThread->nodesLastExplosive > 6000000)
+ thisThread->state = EXPLOSION_NONE;
+
+ return thisThread->state;
+ }
+
+ // Skill structure is used to implement strength limit. If we have an uci_elo then
+ // we convert it to a suitable fractional skill level using anchoring to CCRL Elo
+ // (goldfish 1.13 = 2000) and a fit through Ordo derived Elo for match (TC 60+0.6)
+ // results spanning a wide range of k values.
struct Skill {
- explicit Skill(int l) : level(l) {}
- bool enabled() const { return level < 20; }
- bool time_to_pick(Depth depth) const { return depth == 1 + level; }
+ Skill(int skill_level, int uci_elo) {
+ if (uci_elo)
+ level = std::clamp(std::pow((uci_elo - 1346.6) / 143.4, 1 / 0.806), 0.0, 20.0);
+ else
+ level = double(skill_level);
+ }
+ bool enabled() const { return level < 20.0; }
+ bool time_to_pick(Depth depth) const { return depth == 1 + int(level); }
Move pick_best(size_t multiPV);
- int level;
+ double level;
Move best = MOVE_NONE;
};
- template <NodeType NT>
+ template <NodeType nodeType>
Value search(Position& pos, Stack* ss, Value alpha, Value beta, Depth depth, bool cutNode);
- template <NodeType NT>
+ template <NodeType nodeType>
Value qsearch(Position& pos, Stack* ss, Value alpha, Value beta, Depth depth = 0);
Value value_to_tt(Value v, int ply);
Value value_from_tt(Value v, int ply, int r50c);
void update_pv(Move* pv, Move move, Move* childPv);
void update_continuation_histories(Stack* ss, Piece pc, Square to, int bonus);
- void update_quiet_stats(const Position& pos, Stack* ss, Move move, int bonus, int depth);
+ void update_quiet_stats(const Position& pos, Stack* ss, Move move, int bonus);
void update_all_stats(const Position& pos, Stack* ss, Move bestMove, Value bestValue, Value beta, Square prevSq,
Move* quietsSearched, int quietCount, Move* capturesSearched, int captureCount, Depth depth);
void Search::init() {
for (int i = 1; i < MAX_MOVES; ++i)
- Reductions[i] = int((21.3 + 2 * std::log(Threads.size())) * std::log(i + 0.25 * std::log(i)));
+ Reductions[i] = int((21.9 + std::log(Threads.size()) / 2) * std::log(i));
}
Time.availableNodes += Limits.inc[us] - Threads.nodes_searched();
Thread* bestThread = this;
+ Skill skill = Skill(Options["Skill Level"], Options["UCI_LimitStrength"] ? int(Options["UCI_Elo"]) : 0);
if ( int(Options["MultiPV"]) == 1
&& !Limits.depth
- && !(Skill(Options["Skill Level"]).enabled() || int(Options["UCI_LimitStrength"]))
+ && !skill.enabled()
&& rootMoves[0].pv[0] != MOVE_NONE)
bestThread = Threads.get_best_thread();
bestPreviousScore = bestThread->rootMoves[0].score;
+ bestPreviousAverageScore = bestThread->rootMoves[0].averageScore;
// Send again PV info if we have a new best thread
if (bestThread != this)
// To allow access to (ss-7) up to (ss+2), the stack must be oversized.
// The former is needed to allow update_continuation_histories(ss-1, ...),
// which accesses its argument at ss-6, also near the root.
- // The latter is needed for statScores and killer initialization.
+ // The latter is needed for statScore and killer initialization.
Stack stack[MAX_PLY+10], *ss = stack+7;
Move pv[MAX_PLY+1];
- Value bestValue, alpha, beta, delta;
+ Value alpha, beta, delta;
Move lastBestMove = MOVE_NONE;
Depth lastBestMoveDepth = 0;
MainThread* mainThread = (this == Threads.main() ? Threads.main() : nullptr);
for (int i = 7; i > 0; i--)
(ss-i)->continuationHistory = &this->continuationHistory[0][0][NO_PIECE][0]; // Use as a sentinel
+ for (int i = 0; i <= MAX_PLY + 2; ++i)
+ (ss+i)->ply = i;
+
ss->pv = pv;
bestValue = delta = alpha = -VALUE_INFINITE;
mainThread->iterValue[i] = mainThread->bestPreviousScore;
}
- 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.
- // UCI_Elo is converted to a suitable fractional skill level, using anchoring
- // to CCRL Elo (goldfish 1.13 = 2000) and a fit through Ordo derived Elo
- // for match (TC 60+0.6) results spanning a wide range of k values.
- PRNG rng(now());
- double floatLevel = Options["UCI_LimitStrength"] ?
- std::clamp(std::pow((Options["UCI_Elo"] - 1346.6) / 143.4, 1 / 0.806), 0.0, 20.0) :
- double(Options["Skill Level"]);
- int intLevel = int(floatLevel) +
- ((floatLevel - int(floatLevel)) * 1024 > rng.rand<unsigned>() % 1024 ? 1 : 0);
- Skill skill(intLevel);
+ Skill skill(Options["Skill Level"], Options["UCI_LimitStrength"] ? int(Options["UCI_Elo"]) : 0);
// When playing with strength handicap enable MultiPV search that we will
// use behind the scenes to retrieve a set of possible moves.
multiPV = std::max(multiPV, (size_t)4);
multiPV = std::min(multiPV, rootMoves.size());
- ttHitAverage = TtHitAverageWindow * TtHitAverageResolution / 2;
-
- int ct = int(Options["Contempt"]) * PawnValueEg / 100; // From centipawns
- // In analysis mode, adjust contempt in accordance with user preference
- if (Limits.infinite || Options["UCI_AnalyseMode"])
- ct = Options["Analysis Contempt"] == "Off" ? 0
- : Options["Analysis Contempt"] == "Both" ? ct
- : Options["Analysis Contempt"] == "White" && us == BLACK ? -ct
- : Options["Analysis Contempt"] == "Black" && us == WHITE ? -ct
- : ct;
+ doubleExtensionAverage[WHITE].set(0, 100); // initialize the running average at 0%
+ doubleExtensionAverage[BLACK].set(0, 100); // initialize the running average at 0%
+ complexityAverage.set(232, 1);
- // Evaluation score is from the white point of view
- contempt = (us == WHITE ? make_score(ct, ct / 2)
- : -make_score(ct, ct / 2));
+ nodesLastExplosive = nodes;
+ nodesLastNormal = nodes;
+ state = EXPLOSION_NONE;
+ trend = SCORE_ZERO;
+ optimism[ us] = Value(25);
+ optimism[~us] = -optimism[us];
int searchAgainCounter = 0;
// Reset aspiration window starting size
if (rootDepth >= 4)
{
- Value prev = rootMoves[pvIdx].previousScore;
- delta = Value(17);
+ Value prev = rootMoves[pvIdx].averageScore;
+ delta = Value(17) + int(prev) * prev / 16384;
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 + (113 - ct / 2) * prev / (abs(prev) + 147);
+ // Adjust trend and optimism based on root move's previousScore
+ int tr = sigmoid(prev, 0, 0, 147, 113, 1);
+ trend = (us == WHITE ? make_score(tr, tr / 2)
+ : -make_score(tr, tr / 2));
- contempt = (us == WHITE ? make_score(dct, dct / 2)
- : -make_score(dct, dct / 2));
+ int opt = sigmoid(prev, 0, 25, 147, 14464, 256);
+ optimism[ us] = Value(opt);
+ optimism[~us] = -optimism[us];
}
// Start with a small aspiration window and, in the case of a fail
// high/low, re-search with a bigger window until we don't fail
// high/low anymore.
- failedHighCnt = 0;
+ int failedHighCnt = 0;
while (true)
{
Depth adjustedDepth = std::max(1, rootDepth - failedHighCnt - searchAgainCounter);
- bestValue = Stockfish::search<PV>(rootPos, ss, alpha, beta, adjustedDepth, false);
+ bestValue = Stockfish::search<Root>(rootPos, ss, alpha, beta, adjustedDepth, false);
// Bring the best move to the front. It is critical that sorting
// is done with a stable algorithm because all the values but the
if (skill.enabled() && skill.time_to_pick(rootDepth))
skill.pick_best(multiPV);
+ // Use part of the gained time from a previous stable move for the current move
+ for (Thread* th : Threads)
+ {
+ totBestMoveChanges += th->bestMoveChanges;
+ th->bestMoveChanges = 0;
+ }
+
// Do we have time for the next iteration? Can we stop searching now?
if ( Limits.use_time_management()
&& !Threads.stop
&& !mainThread->stopOnPonderhit)
{
- double fallingEval = (318 + 6 * (mainThread->bestPreviousScore - bestValue)
- + 6 * (mainThread->iterValue[iterIdx] - bestValue)) / 825.0;
+ double fallingEval = (142 + 12 * (mainThread->bestPreviousAverageScore - bestValue)
+ + 6 * (mainThread->iterValue[iterIdx] - bestValue)) / 825.0;
fallingEval = std::clamp(fallingEval, 0.5, 1.5);
// If the bestMove is stable over several iterations, reduce time accordingly
timeReduction = lastBestMoveDepth + 9 < completedDepth ? 1.92 : 0.95;
double reduction = (1.47 + mainThread->previousTimeReduction) / (2.32 * timeReduction);
+ double bestMoveInstability = 1.073 + std::max(1.0, 2.25 - 9.9 / rootDepth)
+ * totBestMoveChanges / Threads.size();
+ int complexity = mainThread->complexityAverage.value();
+ double complexPosition = std::clamp(1.0 + (complexity - 232) / 1750.0, 0.5, 1.5);
- // Use part of the gained time from a previous stable move for the current move
- for (Thread* th : Threads)
- {
- totBestMoveChanges += th->bestMoveChanges;
- th->bestMoveChanges = 0;
- }
- double bestMoveInstability = 1 + 2 * totBestMoveChanges / Threads.size();
-
- double totalTime = Time.optimum() * fallingEval * reduction * bestMoveInstability;
+ double totalTime = Time.optimum() * fallingEval * reduction * bestMoveInstability * complexPosition;
// Cap used time in case of a single legal move for a better viewer experience in tournaments
// yielding correct scores and sufficiently fast moves.
// search<>() is the main search function for both PV and non-PV nodes
- template <NodeType NT>
+ template <NodeType nodeType>
Value search(Position& pos, Stack* ss, Value alpha, Value beta, Depth depth, bool cutNode) {
- constexpr bool PvNode = NT == PV;
- const bool rootNode = PvNode && ss->ply == 0;
+ Thread* thisThread = pos.this_thread();
+
+ // Step 0. Limit search explosion
+ if ( ss->ply > 10
+ && search_explosion(thisThread) == MUST_CALM_DOWN
+ && depth > (ss-1)->depth)
+ depth = (ss-1)->depth;
+
+ constexpr bool PvNode = nodeType != NonPV;
+ constexpr bool rootNode = nodeType == Root;
const Depth maxNextDepth = rootNode ? depth : depth + 1;
// Check if we have an upcoming move which draws by repetition, or
// if the opponent had an alternative move earlier to this position.
- if ( pos.rule50_count() >= 3
+ if ( !rootNode
+ && pos.rule50_count() >= 3
&& alpha < VALUE_DRAW
- && !rootNode
&& pos.has_game_cycle(ss->ply))
{
alpha = value_draw(pos.this_thread());
// Dive into quiescence search when the depth reaches zero
if (depth <= 0)
- return qsearch<NT>(pos, ss, alpha, beta);
+ return qsearch<PvNode ? PV : NonPV>(pos, ss, alpha, beta);
assert(-VALUE_INFINITE <= alpha && alpha < beta && beta <= VALUE_INFINITE);
assert(PvNode || (alpha == beta - 1));
Move ttMove, move, excludedMove, bestMove;
Depth extension, newDepth;
Value bestValue, value, ttValue, eval, maxValue, probCutBeta;
- bool formerPv, givesCheck, improving, didLMR, priorCapture;
- bool captureOrPromotion, doFullDepthSearch, moveCountPruning,
- ttCapture, singularQuietLMR;
+ bool givesCheck, improving, didLMR, priorCapture;
+ bool captureOrPromotion, doFullDepthSearch, moveCountPruning, ttCapture;
Piece movedPiece;
- int moveCount, captureCount, quietCount;
+ int moveCount, captureCount, quietCount, bestMoveCount, improvement, complexity;
// Step 1. Initialize node
- Thread* thisThread = pos.this_thread();
ss->inCheck = pos.checkers();
priorCapture = pos.captured_piece();
Color us = pos.side_to_move();
- moveCount = captureCount = quietCount = ss->moveCount = 0;
+ moveCount = bestMoveCount = captureCount = quietCount = ss->moveCount = 0;
bestValue = -VALUE_INFINITE;
maxValue = VALUE_INFINITE;
if (alpha >= beta)
return alpha;
}
+ else
+ thisThread->rootDelta = beta - alpha;
assert(0 <= ss->ply && ss->ply < MAX_PLY);
- (ss+1)->ply = ss->ply + 1;
- (ss+1)->ttPv = false;
+ (ss+1)->ttPv = false;
(ss+1)->excludedMove = bestMove = MOVE_NONE;
- (ss+2)->killers[0] = (ss+2)->killers[1] = MOVE_NONE;
- Square prevSq = to_sq((ss-1)->currentMove);
+ (ss+2)->killers[0] = (ss+2)->killers[1] = MOVE_NONE;
+ ss->doubleExtensions = (ss-1)->doubleExtensions;
+ ss->depth = depth;
+ Square prevSq = to_sq((ss-1)->currentMove);
+
+ // Update the running average statistics for double extensions
+ thisThread->doubleExtensionAverage[us].update(ss->depth > (ss-1)->depth);
// Initialize statScore to zero for the grandchildren of the current position.
// So statScore is shared between all grandchildren and only the first grandchild
ttValue = ss->ttHit ? value_from_tt(tte->value(), ss->ply, pos.rule50_count()) : VALUE_NONE;
ttMove = rootNode ? thisThread->rootMoves[thisThread->pvIdx].pv[0]
: ss->ttHit ? tte->move() : MOVE_NONE;
+ ttCapture = ttMove && pos.capture_or_promotion(ttMove);
if (!excludedMove)
ss->ttPv = PvNode || (ss->ttHit && tte->is_pv());
- formerPv = ss->ttPv && !PvNode;
-
- // Update low ply history for previous move if we are near root and position is or has been in PV
- if ( ss->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 * ss->ttHit;
// At non-PV nodes we check for an early TT cutoff
if ( !PvNode
&& ss->ttHit
- && tte->depth() >= depth
+ && tte->depth() > depth - (thisThread->id() % 2 == 1)
&& ttValue != VALUE_NONE // Possible in case of TT access race
&& (ttValue >= beta ? (tte->bound() & BOUND_LOWER)
: (tte->bound() & BOUND_UPPER)))
{
- // If ttMove is quiet, update move sorting heuristics on TT hit
+ // If ttMove is quiet, update move sorting heuristics on TT hit (~1 Elo)
if (ttMove)
{
if (ttValue >= beta)
{
- // Bonus for a quiet ttMove that fails high
- if (!pos.capture_or_promotion(ttMove))
- update_quiet_stats(pos, ss, ttMove, stat_bonus(depth), depth);
+ // Bonus for a quiet ttMove that fails high (~3 Elo)
+ if (!ttCapture)
+ update_quiet_stats(pos, ss, ttMove, stat_bonus(depth));
- // Extra penalty for early quiet moves of the previous ply
+ // Extra penalty for early quiet moves of the previous ply (~0 Elo)
if ((ss-1)->moveCount <= 2 && !priorCapture)
update_continuation_histories(ss-1, pos.piece_on(prevSq), prevSq, -stat_bonus(depth + 1));
}
- // Penalty for a quiet ttMove that fails low
- else if (!pos.capture_or_promotion(ttMove))
+ // Penalty for a quiet ttMove that fails low (~1 Elo)
+ else if (!ttCapture)
{
int penalty = -stat_bonus(depth);
thisThread->mainHistory[us][from_to(ttMove)] << penalty;
// Skip early pruning when in check
ss->staticEval = eval = VALUE_NONE;
improving = false;
+ improvement = 0;
+ complexity = 0;
goto moves_loop;
}
else if (ss->ttHit)
if (eval == VALUE_DRAW)
eval = value_draw(thisThread);
- // Can ttValue be used as a better position evaluation?
+ // ttValue can be used as a better position evaluation (~4 Elo)
if ( ttValue != VALUE_NONE
&& (tte->bound() & (ttValue > eval ? BOUND_LOWER : BOUND_UPPER)))
eval = ttValue;
}
else
{
- // In case of null move search use previous static eval with a different sign
- // and addition of two tempos
- if ((ss-1)->currentMove != MOVE_NULL)
- ss->staticEval = eval = evaluate(pos);
- else
- ss->staticEval = eval = -(ss-1)->staticEval + 2 * Tempo;
+ ss->staticEval = eval = evaluate(pos);
// Save static evaluation into transposition table
- tte->save(posKey, VALUE_NONE, ss->ttPv, BOUND_NONE, DEPTH_NONE, MOVE_NONE, eval);
+ if (!excludedMove)
+ tte->save(posKey, VALUE_NONE, ss->ttPv, BOUND_NONE, DEPTH_NONE, MOVE_NONE, eval);
}
- // Use static evaluation difference to improve quiet move ordering
+ // Use static evaluation difference to improve quiet move ordering (~3 Elo)
if (is_ok((ss-1)->currentMove) && !(ss-1)->inCheck && !priorCapture)
{
- int bonus = std::clamp(-depth * 4 * int((ss-1)->staticEval + ss->staticEval - 2 * Tempo), -1000, 1000);
+ int bonus = std::clamp(-16 * int((ss-1)->staticEval + ss->staticEval), -2000, 2000);
thisThread->mainHistory[~us][from_to((ss-1)->currentMove)] << bonus;
}
- // Set up improving flag that is used in various pruning heuristics
- // We define position as improving if static evaluation of position is better
- // Than the previous static evaluation at our turn
- // In case of us being in check at our previous move we look at move prior to it
- improving = (ss-2)->staticEval == VALUE_NONE
- ? ss->staticEval > (ss-4)->staticEval || (ss-4)->staticEval == VALUE_NONE
- : ss->staticEval > (ss-2)->staticEval;
+ // Set up the improvement variable, which is the difference between the current
+ // static evaluation and the previous static evaluation at our turn (if we were
+ // in check at our previous move we look at the move prior to it). The improvement
+ // margin and the improving flag are used in various pruning heuristics.
+ improvement = (ss-2)->staticEval != VALUE_NONE ? ss->staticEval - (ss-2)->staticEval
+ : (ss-4)->staticEval != VALUE_NONE ? ss->staticEval - (ss-4)->staticEval
+ : 200;
- // Step 7. Futility pruning: child node (~50 Elo)
- if ( !PvNode
+ improving = improvement > 0;
+ complexity = abs(ss->staticEval - (us == WHITE ? eg_value(pos.psq_score()) : -eg_value(pos.psq_score())));
+
+ thisThread->complexityAverage.update(complexity);
+
+ // Step 7. Futility pruning: child node (~25 Elo).
+ // The depth condition is important for mate finding.
+ if ( !ss->ttPv
&& depth < 9
&& eval - futility_margin(depth, improving) >= beta
- && eval < VALUE_KNOWN_WIN) // Do not return unproven wins
+ && eval < 15000) // 50% larger than VALUE_KNOWN_WIN, but smaller than TB wins.
return eval;
- // Step 8. Null move search with verification search (~40 Elo)
+ // Step 8. Null move search with verification search (~22 Elo)
if ( !PvNode
&& (ss-1)->currentMove != MOVE_NULL
- && (ss-1)->statScore < 24185
+ && (ss-1)->statScore < 23767
&& eval >= beta
&& eval >= ss->staticEval
- && ss->staticEval >= beta - 24 * depth - 34 * improving + 162 * ss->ttPv + 159
+ && ss->staticEval >= beta - 20 * depth - improvement / 15 + 204 + complexity / 25
&& !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 = (1062 + 68 * depth) / 256 + std::min(int(eval - beta) / 190, 3);
+ Depth R = std::min(int(eval - beta) / 205, 3) + depth / 3 + 4;
ss->currentMove = MOVE_NULL;
ss->continuationHistory = &thisThread->continuationHistory[0][0][NO_PIECE][0];
&& ttValue != VALUE_NONE
&& ttValue < probCutBeta))
{
-
assert(probCutBeta < VALUE_INFINITE);
MovePicker mp(pos, ttMove, probCutBeta - ss->staticEval, &captureHistory);
- int probCutCount = 0;
bool ttPv = ss->ttPv;
ss->ttPv = false;
- while ( (move = mp.next_move()) != MOVE_NONE
- && probCutCount < 2 + 2 * cutNode)
+ while ((move = mp.next_move()) != MOVE_NONE)
if (move != excludedMove && pos.legal(move))
{
assert(pos.capture_or_promotion(move));
assert(depth >= 5);
captureOrPromotion = true;
- probCutCount++;
ss->currentMove = move;
ss->continuationHistory = &thisThread->continuationHistory[ss->inCheck]
ss->ttPv = ttPv;
}
- // Step 10. If the position is not in TT, decrease depth by 2
+ // Step 10. If the position is not in TT, decrease depth by 2 or 1 depending on node type (~3 Elo)
if ( PvNode
&& depth >= 6
&& !ttMove)
depth -= 2;
-moves_loop: // When in check, search starts from here
+ if ( cutNode
+ && depth >= 9
+ && !ttMove)
+ depth--;
- ttCapture = ttMove && pos.capture_or_promotion(ttMove);
+moves_loop: // When in check, search starts here
- // Step 11. A small Probcut idea, when we are in check
- probCutBeta = beta + 400;
+ // Step 11. A small Probcut idea, when we are in check (~0 Elo)
+ probCutBeta = beta + 409;
if ( ss->inCheck
&& !PvNode
&& depth >= 4
Move countermove = thisThread->counterMoves[pos.piece_on(prevSq)][prevSq];
MovePicker mp(pos, ttMove, depth, &thisThread->mainHistory,
- &thisThread->lowPlyHistory,
&captureHistory,
contHist,
countermove,
- ss->killers,
- ss->ply);
+ ss->killers);
value = bestValue;
- singularQuietLMR = moveCountPruning = false;
+ moveCountPruning = false;
// Indicate PvNodes that will probably fail low if the node was searched
// at a depth equal or greater than the current depth, and the result of this search was a fail low.
// Calculate new depth for this move
newDepth = depth - 1;
- // Step 13. Pruning at shallow depth (~200 Elo)
+ Value delta = beta - alpha;
+
+ // Step 13. Pruning at shallow depth (~98 Elo). Depth conditions are important for mate finding.
if ( !rootNode
&& pos.non_pawn_material(us)
&& bestValue > VALUE_TB_LOSS_IN_MAX_PLY)
{
- // Skip quiet moves if movecount exceeds our FutilityMoveCount threshold
+ // Skip quiet moves if movecount exceeds our FutilityMoveCount threshold (~7 Elo)
moveCountPruning = moveCount >= futility_move_count(improving, depth);
// Reduced depth of the next LMR search
- int lmrDepth = std::max(newDepth - reduction(improving, depth, moveCount), 0);
+ int lmrDepth = std::max(newDepth - reduction(improving, depth, moveCount, delta, thisThread->rootDelta), 0);
if ( captureOrPromotion
|| givesCheck)
{
- // Capture history based pruning when the move doesn't give check
- if ( !givesCheck
- && lmrDepth < 1
- && captureHistory[movedPiece][to_sq(move)][type_of(pos.piece_on(to_sq(move)))] < 0)
+ // Futility pruning for captures (~0 Elo)
+ if ( !pos.empty(to_sq(move))
+ && !givesCheck
+ && !PvNode
+ && lmrDepth < 6
+ && !ss->inCheck
+ && ss->staticEval + 342 + 238 * lmrDepth + PieceValue[EG][pos.piece_on(to_sq(move))]
+ + captureHistory[movedPiece][to_sq(move)][type_of(pos.piece_on(to_sq(move)))] / 8 < alpha)
continue;
- // SEE based pruning
- if (!pos.see_ge(move, Value(-218) * depth)) // (~25 Elo)
+ // SEE based pruning (~9 Elo)
+ if (!pos.see_ge(move, Value(-217) * depth))
continue;
}
else
{
- // Countermoves based pruning (~20 Elo)
- if ( lmrDepth < 4 + ((ss-1)->statScore > 0 || (ss-1)->moveCount == 1)
- && (*contHist[0])[movedPiece][to_sq(move)] < CounterMovePruneThreshold
- && (*contHist[1])[movedPiece][to_sq(move)] < CounterMovePruneThreshold)
+ int history = (*contHist[0])[movedPiece][to_sq(move)]
+ + (*contHist[1])[movedPiece][to_sq(move)]
+ + (*contHist[3])[movedPiece][to_sq(move)];
+
+ // Continuation history based pruning (~2 Elo)
+ if ( lmrDepth < 5
+ && history < -3875 * (depth - 1))
continue;
- // Futility pruning: parent node (~5 Elo)
- if ( lmrDepth < 7
- && !ss->inCheck
- && ss->staticEval + 174 + 157 * lmrDepth <= alpha
- && (*contHist[0])[movedPiece][to_sq(move)]
- + (*contHist[1])[movedPiece][to_sq(move)]
- + (*contHist[3])[movedPiece][to_sq(move)]
- + (*contHist[5])[movedPiece][to_sq(move)] / 3 < 28255)
+ history += thisThread->mainHistory[us][from_to(move)];
+
+ // Futility pruning: parent node (~9 Elo)
+ if ( !ss->inCheck
+ && lmrDepth < 8
+ && ss->staticEval + 138 + 137 * lmrDepth + history / 64 <= alpha)
continue;
- // Prune moves with negative SEE (~20 Elo)
- if (!pos.see_ge(move, Value(-(30 - std::min(lmrDepth, 18)) * lmrDepth * lmrDepth)))
+ // Prune moves with negative SEE (~3 Elo)
+ if (!pos.see_ge(move, Value(-21 * lmrDepth * lmrDepth - 21 * lmrDepth)))
continue;
}
}
- // Step 14. Extensions (~75 Elo)
+ // Step 14. Extensions (~66 Elo)
- // Singular extension search (~70 Elo). If all moves but one fail low on a
+ // Singular extension search (~58 Elo). 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 is singular and should be extended. To verify this we do
// a reduced search on all the other moves but the ttMove and if the
// result is lower than ttValue minus a margin, then we will extend the ttMove.
- if ( depth >= 7
+ if ( !rootNode
+ && depth >= 6 + 2 * (PvNode && tte->is_pv())
&& move == ttMove
- && !rootNode
&& !excludedMove // Avoid recursive singular search
/* && ttValue != VALUE_NONE Already implicit in the next condition */
&& abs(ttValue) < VALUE_KNOWN_WIN
&& (tte->bound() & BOUND_LOWER)
&& tte->depth() >= depth - 3)
{
- Value singularBeta = ttValue - ((formerPv + 4) * depth) / 2;
- Depth singularDepth = (depth - 1 + 3 * formerPv) / 2;
+ Value singularBeta = ttValue - 3 * depth;
+ Depth singularDepth = (depth - 1) / 2;
ss->excludedMove = move;
value = search<NonPV>(pos, ss, singularBeta - 1, singularBeta, singularDepth, cutNode);
if (value < singularBeta)
{
extension = 1;
- singularQuietLMR = !ttCapture;
- if (!PvNode && value < singularBeta - 140)
+
+ // Avoid search explosion by limiting the number of double extensions
+ if ( !PvNode
+ && value < singularBeta - 75
+ && ss->doubleExtensions <= 6)
extension = 2;
}
else if (singularBeta >= beta)
return singularBeta;
- // 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.
+ // If the eval of ttMove is greater than beta, we reduce it (negative extension)
else if (ttValue >= beta)
- {
- ss->excludedMove = move;
- value = search<NonPV>(pos, ss, beta - 1, beta, (depth + 3) / 2, cutNode);
- ss->excludedMove = MOVE_NONE;
-
- if (value >= beta)
- return beta;
- }
+ extension = -2;
}
+ // Check extensions (~1 Elo)
+ else if ( givesCheck
+ && depth > 6
+ && abs(ss->staticEval) > 100)
+ extension = 1;
+
+ // Quiet ttMove extensions (~0 Elo)
+ else if ( PvNode
+ && move == ttMove
+ && move == ss->killers[0]
+ && (*contHist[0])[movedPiece][to_sq(move)] >= 10000)
+ extension = 1;
+
// Add extension to new depth
newDepth += extension;
+ ss->doubleExtensions = (ss-1)->doubleExtensions + (extension == 2);
// Speculative prefetch as early as possible
prefetch(TT.first_entry(pos.key_after(move)));
// Step 15. Make the move
pos.do_move(move, st, givesCheck);
- // Step 16. Late moves reduction / extension (LMR, ~200 Elo)
+ bool doDeeperSearch = false;
+
+ // Step 16. Late moves reduction / extension (LMR, ~98 Elo)
// We use various heuristics for the sons of a node after the first son has
// been searched. In general we would like to reduce them, but there are many
// cases where we extend a son if it has good chances to be "interesting".
if ( depth >= 3
&& moveCount > 1 + 2 * rootNode
- && ( !captureOrPromotion
- || moveCountPruning
- || ss->staticEval + PieceValue[EG][pos.captured_piece()] <= alpha
- || cutNode
- || (!PvNode && !formerPv && captureHistory[movedPiece][to_sq(move)][type_of(pos.captured_piece())] < 3678)
- || thisThread->ttHitAverage < 432 * TtHitAverageResolution * TtHitAverageWindow / 1024)
- && (!PvNode || ss->ply > 1 || thisThread->id() % 4 != 3))
+ && ( !ss->ttPv
+ || !captureOrPromotion
+ || (cutNode && (ss-1)->moveCount > 1)))
{
- Depth r = reduction(improving, depth, moveCount);
+ Depth r = reduction(improving, depth, moveCount, delta, thisThread->rootDelta);
- // Decrease reduction if the ttHit running average is large
- if (thisThread->ttHitAverage > 537 * TtHitAverageResolution * TtHitAverageWindow / 1024)
+ // Decrease reduction at some PvNodes (~2 Elo)
+ if ( PvNode
+ && bestMoveCount <= 3)
r--;
// Decrease reduction if position is or has been on the PV
- // and node is not likely to fail low. (~10 Elo)
+ // and node is not likely to fail low. (~3 Elo)
if ( ss->ttPv
&& !likelyFailLow)
r -= 2;
- // Increase reduction at root and non-PV nodes when the best move does not change frequently
- if ( (rootNode || !PvNode)
- && thisThread->rootDepth > 10
- && thisThread->bestMoveChanges <= 2)
- r++;
-
// Decrease reduction if opponent's move count is high (~1 Elo)
if ((ss-1)->moveCount > 13)
r--;
- // Decrease reduction if ttMove has been singularly extended (~1 Elo)
- if (singularQuietLMR)
- r--;
+ // Increase reduction for cut nodes (~3 Elo)
+ if (cutNode && move != ss->killers[0])
+ r += 2;
- if (!captureOrPromotion)
- {
- // Increase reduction if ttMove is a capture (~3 Elo)
- if (ttCapture)
- r++;
-
- // Increase reduction at root if failing high
- r += rootNode ? thisThread->failedHighCnt * thisThread->failedHighCnt * moveCount / 512 : 0;
-
- // Increase reduction for cut nodes (~10 Elo)
- if (cutNode)
- r += 2;
-
- 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)]
- - 4741;
-
- // Decrease/increase reduction by comparing opponent's stat score (~10 Elo)
- if (ss->statScore >= -89 && (ss-1)->statScore < -116)
- r--;
-
- else if ((ss-1)->statScore >= -112 && ss->statScore < -100)
- r++;
-
- // Decrease/increase reduction for moves with a good/bad history (~30 Elo)
- // If we are not in check use statScore, but if we are in check we use
- // the sum of main history and first continuation history with an offset.
- if (ss->inCheck)
- r -= (thisThread->mainHistory[us][from_to(move)]
- + (*contHist[0])[movedPiece][to_sq(move)] - 3833) / 16384;
- else
- r -= ss->statScore / 14790;
- }
+ // Increase reduction if ttMove is a capture (~3 Elo)
+ if (ttCapture)
+ r++;
+
+ 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)]
+ - 4923;
+
+ // Decrease/increase reduction for moves with a good/bad history (~30 Elo)
+ r -= ss->statScore / 14721;
- // In general we want to cap the LMR depth search at newDepth. But if
- // reductions are really negative and movecount is low, we allow this move
- // to be searched deeper than the first move.
- Depth d = std::clamp(newDepth - r, 1, newDepth + (r < -1 && moveCount <= 5));
+ // In general we want to cap the LMR depth search at newDepth. But if reductions
+ // are really negative and movecount is low, we allow this move to be searched
+ // deeper than the first move (this may lead to hidden double extensions).
+ int deeper = r >= -1 ? 0
+ : moveCount <= 5 ? 2
+ : PvNode && depth > 6 ? 1
+ : cutNode && moveCount <= 7 ? 1
+ : 0;
+
+ Depth d = std::clamp(newDepth - r, 1, newDepth + deeper);
value = -search<NonPV>(pos, ss+1, -(alpha+1), -alpha, d, true);
// If the son is reduced and fails high it will be re-searched at full depth
doFullDepthSearch = value > alpha && d < newDepth;
+ doDeeperSearch = value > (alpha + 62 + 20 * (newDepth - d));
didLMR = true;
}
else
// Step 17. Full depth search when LMR is skipped or fails high
if (doFullDepthSearch)
{
- value = -search<NonPV>(pos, ss+1, -(alpha+1), -alpha, newDepth, !cutNode);
+ value = -search<NonPV>(pos, ss+1, -(alpha+1), -alpha, newDepth + doDeeperSearch, !cutNode);
// If the move passed LMR update its stats
if (didLMR && !captureOrPromotion)
RootMove& rm = *std::find(thisThread->rootMoves.begin(),
thisThread->rootMoves.end(), move);
+ rm.averageScore = rm.averageScore != -VALUE_INFINITE ? (2 * value + rm.averageScore) / 3 : value;
+
// PV move or new best move?
if (moveCount == 1 || value > alpha)
{
for (Move* m = (ss+1)->pv; *m != MOVE_NONE; ++m)
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 and LMR
- if (moveCount > 1)
+ // We record how often the best move has been changed in each iteration.
+ // This information is used for time management. In MultiPV mode,
+ // we must take care to only do this for the first PV line.
+ if ( moveCount > 1
+ && !thisThread->pvIdx)
++thisThread->bestMoveChanges;
}
else
update_pv(ss->pv, move, (ss+1)->pv);
if (PvNode && value < beta) // Update alpha! Always alpha < beta
+ {
alpha = value;
+ bestMoveCount++;
+ }
else
{
assert(value >= beta); // Fail high
- ss->statScore = 0;
break;
}
}
// Bonus for prior countermove that caused the fail low
else if ( (depth >= 3 || PvNode)
&& !priorCapture)
- update_continuation_histories(ss-1, pos.piece_on(prevSq), prevSq, stat_bonus(depth));
+ {
+ //Assign extra bonus if current node is PvNode or cutNode
+ //or fail low was really bad
+ bool extraBonus = PvNode
+ || cutNode
+ || bestValue < alpha - 94 * depth;
+
+ update_continuation_histories(ss-1, pos.piece_on(prevSq), prevSq, stat_bonus(depth) * (1 + extraBonus));
+ }
if (PvNode)
bestValue = std::min(bestValue, maxValue);
// 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>
+ template <NodeType nodeType>
Value qsearch(Position& pos, Stack* ss, Value alpha, Value beta, Depth depth) {
- constexpr bool PvNode = NT == PV;
+ static_assert(nodeType != Root);
+ constexpr bool PvNode = nodeType == PV;
assert(alpha >= -VALUE_INFINITE && alpha < beta && beta <= VALUE_INFINITE);
assert(PvNode || (alpha == beta - 1));
Key posKey;
Move ttMove, move, bestMove;
Depth ttDepth;
- Value bestValue, value, ttValue, futilityValue, futilityBase, oldAlpha;
+ Value bestValue, value, ttValue, futilityValue, futilityBase;
bool pvHit, givesCheck, captureOrPromotion;
int moveCount;
if (PvNode)
{
- oldAlpha = alpha; // To flag BOUND_EXACT when eval above alpha and no available moves
(ss+1)->pv = pv;
ss->pv[0] = MOVE_NONE;
}
Thread* thisThread = pos.this_thread();
- (ss+1)->ply = ss->ply + 1;
bestMove = MOVE_NONE;
ss->inCheck = pos.checkers();
moveCount = 0;
if ((ss->staticEval = bestValue = tte->eval()) == VALUE_NONE)
ss->staticEval = bestValue = evaluate(pos);
- // Can ttValue be used as a better position evaluation?
+ // ttValue can be used as a better position evaluation (~7 Elo)
if ( ttValue != VALUE_NONE
&& (tte->bound() & (ttValue > bestValue ? BOUND_LOWER : BOUND_UPPER)))
bestValue = ttValue;
}
else
// In case of null move search use previous static eval with a different sign
- // and addition of two tempos
ss->staticEval = bestValue =
(ss-1)->currentMove != MOVE_NULL ? evaluate(pos)
- : -(ss-1)->staticEval + 2 * Tempo;
+ : -(ss-1)->staticEval;
// Stand pat. Return immediately if static value is at least beta
if (bestValue >= beta)
// Initialize a MovePicker object for the current position, and prepare
// to search the moves. Because the depth is <= 0 here, only captures,
- // queen and checking knight promotions, and other checks(only if depth >= DEPTH_QS_CHECKS)
+ // queen promotions, and other checks (only if depth >= DEPTH_QS_CHECKS)
// will be generated.
+ Square prevSq = to_sq((ss-1)->currentMove);
MovePicker mp(pos, ttMove, depth, &thisThread->mainHistory,
&thisThread->captureHistory,
contHist,
- to_sq((ss-1)->currentMove));
+ prevSq);
// Loop through the moves until no moves remain or a beta cutoff occurs
while ((move = mp.next_move()) != MOVE_NONE)
{
assert(is_ok(move));
+ // Check for legality
+ if (!pos.legal(move))
+ continue;
+
givesCheck = pos.gives_check(move);
captureOrPromotion = pos.capture_or_promotion(move);
moveCount++;
- // Futility pruning and moveCount pruning
+ // Futility pruning and moveCount pruning (~5 Elo)
if ( bestValue > VALUE_TB_LOSS_IN_MAX_PLY
&& !givesCheck
+ && to_sq(move) != prevSq
&& futilityBase > -VALUE_KNOWN_WIN
&& type_of(move) != PROMOTION)
{
}
}
- // Do not search moves with negative SEE values
+ // Do not search moves with negative SEE values (~5 Elo)
if ( bestValue > VALUE_TB_LOSS_IN_MAX_PLY
&& !pos.see_ge(move))
continue;
// Speculative prefetch as early as possible
prefetch(TT.first_entry(pos.key_after(move)));
- // Check for legality just before making the move
- if (!pos.legal(move))
- {
- moveCount--;
- continue;
- }
-
ss->currentMove = move;
ss->continuationHistory = &thisThread->continuationHistory[ss->inCheck]
[captureOrPromotion]
[pos.moved_piece(move)]
[to_sq(move)];
- // CounterMove based pruning
+ // Continuation history based pruning (~2 Elo)
if ( !captureOrPromotion
&& bestValue > VALUE_TB_LOSS_IN_MAX_PLY
&& (*contHist[0])[pos.moved_piece(move)][to_sq(move)] < CounterMovePruneThreshold
// Make and search the move
pos.do_move(move, st, givesCheck);
- value = -qsearch<NT>(pos, ss+1, -beta, -alpha, depth - 1);
+ value = -qsearch<nodeType>(pos, ss+1, -beta, -alpha, depth - 1);
pos.undo_move(move);
assert(value > -VALUE_INFINITE && value < VALUE_INFINITE);
// Save gathered info in transposition table
tte->save(posKey, value_to_tt(bestValue, ss->ply), pvHit,
- bestValue >= beta ? BOUND_LOWER :
- PvNode && bestValue > oldAlpha ? BOUND_EXACT : BOUND_UPPER,
+ bestValue >= beta ? BOUND_LOWER : BOUND_UPPER,
ttDepth, bestMove, ss->staticEval);
assert(bestValue > -VALUE_INFINITE && bestValue < VALUE_INFINITE);
PieceType captured = type_of(pos.piece_on(to_sq(bestMove)));
bonus1 = stat_bonus(depth + 1);
- bonus2 = bestValue > beta + PawnValueMg ? bonus1 // larger bonus
- : std::min(bonus1, stat_bonus(depth)); // smaller bonus
+ bonus2 = bestValue > beta + PawnValueMg ? bonus1 // larger bonus
+ : stat_bonus(depth); // smaller bonus
if (!pos.capture_or_promotion(bestMove))
{
// Increase stats for the best move in case it was a quiet move
- update_quiet_stats(pos, ss, bestMove, bonus2, depth);
+ update_quiet_stats(pos, ss, bestMove, bonus2);
// Decrease stats for all non-best quiet moves
for (int i = 0; i < quietCount; ++i)
// update_quiet_stats() updates move sorting heuristics
- void update_quiet_stats(const Position& pos, Stack* ss, Move move, int bonus, int depth) {
+ void update_quiet_stats(const Position& pos, Stack* ss, Move move, int bonus) {
// Update killers
if (ss->killers[0] != move)
thisThread->mainHistory[us][from_to(move)] << bonus;
update_continuation_histories(ss, pos.moved_piece(move), to_sq(move), bonus);
- // Penalty for reversed move in case of moved piece not being a pawn
- if (type_of(pos.moved_piece(move)) != PAWN)
- thisThread->mainHistory[us][from_to(reverse_move(move))] << -bonus;
-
// Update countermove history
if (is_ok((ss-1)->currentMove))
{
Square prevSq = to_sq((ss-1)->currentMove);
thisThread->counterMoves[pos.piece_on(prevSq)][prevSq] = move;
}
-
- // Update low ply history
- if (depth > 11 && ss->ply < MAX_LPH)
- thisThread->lowPlyHistory[ss->ply][from_to(move)] << stat_bonus(depth - 7);
}
// When playing with strength handicap, choose best move among a set of RootMoves
// RootMoves are already sorted by score in descending order
Value topScore = rootMoves[0].score;
int delta = std::min(topScore - rootMoves[multiPV - 1].score, PawnValueMg);
- int weakness = 120 - 2 * level;
int maxScore = -VALUE_INFINITE;
+ double weakness = 120 - 2 * level;
// Choose best move. For each move score we add two terms, both dependent on
// weakness. One is deterministic and bigger for weaker levels, and one is
for (size_t i = 0; i < multiPV; ++i)
{
// This is our magic formula
- int push = ( weakness * int(topScore - rootMoves[i].score)
- + delta * (rng.rand<unsigned>() % weakness)) / 128;
+ int push = int(( weakness * int(topScore - rootMoves[i].score)
+ + delta * (rng.rand<unsigned>() % int(weakness))) / 128);
if (rootMoves[i].score + push >= maxScore)
{