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BadFish/src/search.cpp
Michael Chaly 7b49f9dd70 Tweak multicut 
This patch is an original patch by author of Altair
(https://github.com/Alex2262/AltairChessEngine) chess engine.

It allows to produce more aggressive multicut compared to master by changing
condition it needs to fulfil and also returns bigger value.  Also has applied
matetrack fix on top.

Passed STC:
https://tests.stockfishchess.org/tests/view/667223ab602682471b0650e2
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 50048 W: 13200 L: 12860 D: 23988
Ptnml(0-2): 181, 5822, 12679, 6160, 182

Passed LTC:
https://tests.stockfishchess.org/tests/view/6672f777602682471b06515d
LLR: 2.97 (-2.94,2.94) <0.50,2.50>
Total: 706380 W: 179707 L: 177981 D: 348692
Ptnml(0-2): 656, 79250, 191665, 80950, 669

closes https://github.com/official-stockfish/Stockfish/pull/5421

bench 1148966
2024-07-01 19:56:38 +02:00

2031 lines
81 KiB
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/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2024 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
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
Stockfish is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "search.h"
#include <algorithm>
#include <array>
#include <atomic>
#include <cassert>
#include <cmath>
#include <cstdint>
#include <cstdlib>
#include <initializer_list>
#include <string>
#include <utility>
#include "evaluate.h"
#include "misc.h"
#include "movegen.h"
#include "movepick.h"
#include "nnue/network.h"
#include "nnue/nnue_accumulator.h"
#include "nnue/nnue_common.h"
#include "nnue/nnue_misc.h"
#include "position.h"
#include "syzygy/tbprobe.h"
#include "thread.h"
#include "timeman.h"
#include "tt.h"
#include "types.h"
#include "uci.h"
#include "ucioption.h"
namespace Stockfish {
namespace TB = Tablebases;
using Eval::evaluate;
using namespace Search;
namespace {
static constexpr double EvalLevel[10] = {0.981, 0.956, 0.895, 0.949, 0.913,
0.942, 0.933, 0.890, 0.984, 0.941};
// Futility margin
Value futility_margin(Depth d, bool noTtCutNode, bool improving, bool oppWorsening) {
Value futilityMult = 109 - 40 * noTtCutNode;
Value improvingDeduction = 59 * improving * futilityMult / 32;
Value worseningDeduction = 328 * oppWorsening * futilityMult / 1024;
return futilityMult * d - improvingDeduction - worseningDeduction;
}
constexpr int futility_move_count(bool improving, Depth depth) {
return improving ? (3 + depth * depth) : (3 + depth * depth) / 2;
}
// Add correctionHistory value to raw staticEval and guarantee evaluation does not hit the tablebase range
Value to_corrected_static_eval(Value v, const Worker& w, const Position& pos) {
auto cv = w.correctionHistory[pos.side_to_move()][pawn_structure_index<Correction>(pos)];
v += cv / 10;
return std::clamp(v, VALUE_TB_LOSS_IN_MAX_PLY + 1, VALUE_TB_WIN_IN_MAX_PLY - 1);
}
// History and stats update bonus, based on depth
int stat_bonus(Depth d) { return std::clamp(186 * d - 285, 20, 1524); }
// History and stats update malus, based on depth
int stat_malus(Depth d) { return (d < 4 ? 707 * d - 260 : 2073); }
// Add a small random component to draw evaluations to avoid 3-fold blindness
Value value_draw(size_t nodes) { return VALUE_DRAW - 1 + Value(nodes & 0x2); }
// Skill structure is used to implement strength limit. If we have a UCI_Elo,
// we convert it to an appropriate skill level, anchored to the Stash engine.
// This method is based on a fit of the Elo results for games played between
// Stockfish at various skill levels and various versions of the Stash engine.
// Skill 0 .. 19 now covers CCRL Blitz Elo from 1320 to 3190, approximately
// Reference: https://github.com/vondele/Stockfish/commit/a08b8d4e9711c2
struct Skill {
Skill(int skill_level, int uci_elo) {
if (uci_elo)
{
double e = double(uci_elo - 1320) / (3190 - 1320);
level = std::clamp((((37.2473 * e - 40.8525) * e + 22.2943) * e - 0.311438), 0.0, 19.0);
}
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(const RootMoves&, size_t multiPV);
double level;
Move best = Move::none();
};
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, const Move* childPv);
void update_continuation_histories(Stack* ss, Piece pc, Square to, int bonus);
void update_refutations(const Position& pos, Stack* ss, Search::Worker& workerThread, Move move);
void update_quiet_histories(
const Position& pos, Stack* ss, Search::Worker& workerThread, Move move, int bonus);
void update_quiet_stats(
const Position& pos, Stack* ss, Search::Worker& workerThread, Move move, int bonus);
void update_all_stats(const Position& pos,
Stack* ss,
Search::Worker& workerThread,
Move bestMove,
Value bestValue,
Value beta,
Square prevSq,
Move* quietsSearched,
int quietCount,
Move* capturesSearched,
int captureCount,
Depth depth);
} // namespace
Search::Worker::Worker(SharedState& sharedState,
std::unique_ptr<ISearchManager> sm,
size_t threadId,
NumaReplicatedAccessToken token) :
// Unpack the SharedState struct into member variables
threadIdx(threadId),
numaAccessToken(token),
manager(std::move(sm)),
options(sharedState.options),
threads(sharedState.threads),
tt(sharedState.tt),
networks(sharedState.networks),
refreshTable(networks[token]) {
clear();
}
void Search::Worker::start_searching() {
// Non-main threads go directly to iterative_deepening()
if (!is_mainthread())
{
iterative_deepening();
return;
}
main_manager()->tm.init(limits, rootPos.side_to_move(), rootPos.game_ply(), options,
main_manager()->originalTimeAdjust);
tt.new_search();
if (rootMoves.empty())
{
rootMoves.emplace_back(Move::none());
main_manager()->updates.onUpdateNoMoves(
{0, {rootPos.checkers() ? -VALUE_MATE : VALUE_DRAW, rootPos}});
}
else
{
threads.start_searching(); // start non-main threads
iterative_deepening(); // main thread start searching
}
// When we reach the maximum depth, we can arrive here without a raise of
// threads.stop. However, if we are pondering or in an infinite search,
// the UCI protocol states that we shouldn't print the best move before the
// GUI sends a "stop" or "ponderhit" command. We therefore simply wait here
// until the GUI sends one of those commands.
while (!threads.stop && (main_manager()->ponder || limits.infinite))
{} // Busy wait for a stop or a ponder reset
// Stop the threads if not already stopped (also raise the stop if
// "ponderhit" just reset threads.ponder).
threads.stop = true;
// Wait until all threads have finished
threads.wait_for_search_finished();
// When playing in 'nodes as time' mode, subtract the searched nodes from
// the available ones before exiting.
if (limits.npmsec)
main_manager()->tm.advance_nodes_time(threads.nodes_searched()
- limits.inc[rootPos.side_to_move()]);
Worker* bestThread = this;
Skill skill =
Skill(options["Skill Level"], options["UCI_LimitStrength"] ? int(options["UCI_Elo"]) : 0);
if (int(options["MultiPV"]) == 1 && !limits.depth && !limits.mate && !skill.enabled()
&& rootMoves[0].pv[0] != Move::none())
bestThread = threads.get_best_thread()->worker.get();
main_manager()->bestPreviousScore = bestThread->rootMoves[0].score;
main_manager()->bestPreviousAverageScore = bestThread->rootMoves[0].averageScore;
// Send again PV info if we have a new best thread
if (bestThread != this)
main_manager()->pv(*bestThread, threads, tt, bestThread->completedDepth);
std::string ponder;
if (bestThread->rootMoves[0].pv.size() > 1
|| bestThread->rootMoves[0].extract_ponder_from_tt(tt, rootPos))
ponder = UCIEngine::move(bestThread->rootMoves[0].pv[1], rootPos.is_chess960());
auto bestmove = UCIEngine::move(bestThread->rootMoves[0].pv[0], rootPos.is_chess960());
main_manager()->updates.onBestmove(bestmove, ponder);
}
// Main iterative deepening loop. It calls search()
// repeatedly with increasing depth until the allocated thinking time has been
// consumed, the user stops the search, or the maximum search depth is reached.
void Search::Worker::iterative_deepening() {
SearchManager* mainThread = (is_mainthread() ? main_manager() : nullptr);
Move pv[MAX_PLY + 1];
Depth lastBestMoveDepth = 0;
Value lastBestScore = -VALUE_INFINITE;
auto lastBestPV = std::vector{Move::none()};
Value alpha, beta;
Value bestValue = -VALUE_INFINITE;
Color us = rootPos.side_to_move();
double timeReduction = 1, totBestMoveChanges = 0;
int delta, iterIdx = 0;
// Allocate stack with extra size to allow access from (ss - 7) to (ss + 2):
// (ss - 7) is needed for update_continuation_histories(ss - 1) which accesses (ss - 6),
// (ss + 2) is needed for initialization of cutOffCnt and killers.
Stack stack[MAX_PLY + 10] = {};
Stack* ss = stack + 7;
for (int i = 7; i > 0; --i)
{
(ss - i)->continuationHistory =
&this->continuationHistory[0][0][NO_PIECE][0]; // Use as a sentinel
(ss - i)->staticEval = VALUE_NONE;
}
for (int i = 0; i <= MAX_PLY + 2; ++i)
(ss + i)->ply = i;
ss->pv = pv;
if (mainThread)
{
if (mainThread->bestPreviousScore == VALUE_INFINITE)
mainThread->iterValue.fill(VALUE_ZERO);
else
mainThread->iterValue.fill(mainThread->bestPreviousScore);
}
size_t multiPV = size_t(options["MultiPV"]);
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.
if (skill.enabled())
multiPV = std::max(multiPV, size_t(4));
multiPV = std::min(multiPV, rootMoves.size());
int searchAgainCounter = 0;
// Iterative deepening loop until requested to stop or the target depth is reached
while (++rootDepth < MAX_PLY && !threads.stop
&& !(limits.depth && mainThread && rootDepth > limits.depth))
{
// Age out PV variability metric
if (mainThread)
totBestMoveChanges /= 2;
// Save the last iteration's scores before the first PV line is searched and
// all the move scores except the (new) PV are set to -VALUE_INFINITE.
for (RootMove& rm : rootMoves)
rm.previousScore = rm.score;
size_t pvFirst = 0;
pvLast = 0;
if (!threads.increaseDepth)
searchAgainCounter++;
// MultiPV loop. We perform a full root search for each PV line
for (pvIdx = 0; pvIdx < multiPV; ++pvIdx)
{
if (pvIdx == pvLast)
{
pvFirst = pvLast;
for (pvLast++; pvLast < rootMoves.size(); pvLast++)
if (rootMoves[pvLast].tbRank != rootMoves[pvFirst].tbRank)
break;
}
// Reset UCI info selDepth for each depth and each PV line
selDepth = 0;
// Reset aspiration window starting size
Value avg = rootMoves[pvIdx].averageScore;
delta = 9 + avg * avg / 10182;
alpha = std::max(avg - delta, -VALUE_INFINITE);
beta = std::min(avg + delta, VALUE_INFINITE);
// Adjust optimism based on root move's averageScore (~4 Elo)
optimism[us] = 127 * avg / (std::abs(avg) + 86);
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.
int failedHighCnt = 0;
while (true)
{
// Adjust the effective depth searched, but ensure at least one effective increment
// for every four searchAgain steps (see issue #2717).
Depth adjustedDepth =
std::max(1, rootDepth - failedHighCnt - 3 * (searchAgainCounter + 1) / 4);
rootDelta = beta - alpha;
bestValue = 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
// first and eventually the new best one is set to -VALUE_INFINITE
// and we want to keep the same order for all the moves except the
// new PV that goes to the front. Note that in the case of MultiPV
// search the already searched PV lines are preserved.
std::stable_sort(rootMoves.begin() + pvIdx, rootMoves.begin() + pvLast);
// If search has been stopped, we break immediately. Sorting is
// safe because RootMoves is still valid, although it refers to
// the previous iteration.
if (threads.stop)
break;
// When failing high/low give some update (without cluttering
// the UI) before a re-search.
if (mainThread && multiPV == 1 && (bestValue <= alpha || bestValue >= beta)
&& elapsed_time() > 3000)
main_manager()->pv(*this, threads, tt, rootDepth);
// In case of failing low/high increase aspiration window and
// re-search, otherwise exit the loop.
if (bestValue <= alpha)
{
beta = (alpha + beta) / 2;
alpha = std::max(bestValue - delta, -VALUE_INFINITE);
failedHighCnt = 0;
if (mainThread)
mainThread->stopOnPonderhit = false;
}
else if (bestValue >= beta)
{
beta = std::min(bestValue + delta, VALUE_INFINITE);
++failedHighCnt;
}
else
break;
delta += delta / 3;
assert(alpha >= -VALUE_INFINITE && beta <= VALUE_INFINITE);
}
// Sort the PV lines searched so far and update the GUI
std::stable_sort(rootMoves.begin() + pvFirst, rootMoves.begin() + pvIdx + 1);
if (mainThread
&& (threads.stop || pvIdx + 1 == multiPV || elapsed_time() > 3000)
// A thread that aborted search can have mated-in/TB-loss PV and score
// that cannot be trusted, i.e. it can be delayed or refuted if we would have
// had time to fully search other root-moves. Thus we suppress this output and
// below pick a proven score/PV for this thread (from the previous iteration).
&& !(threads.abortedSearch && rootMoves[0].uciScore <= VALUE_TB_LOSS_IN_MAX_PLY))
main_manager()->pv(*this, threads, tt, rootDepth);
if (threads.stop)
break;
}
if (!threads.stop)
completedDepth = rootDepth;
// We make sure not to pick an unproven mated-in score,
// in case this thread prematurely stopped search (aborted-search).
if (threads.abortedSearch && rootMoves[0].score != -VALUE_INFINITE
&& rootMoves[0].score <= VALUE_TB_LOSS_IN_MAX_PLY)
{
// Bring the last best move to the front for best thread selection.
Utility::move_to_front(rootMoves, [&lastBestPV = std::as_const(lastBestPV)](
const auto& rm) { return rm == lastBestPV[0]; });
rootMoves[0].pv = lastBestPV;
rootMoves[0].score = rootMoves[0].uciScore = lastBestScore;
}
else if (rootMoves[0].pv[0] != lastBestPV[0])
{
lastBestPV = rootMoves[0].pv;
lastBestScore = rootMoves[0].score;
lastBestMoveDepth = rootDepth;
}
if (!mainThread)
continue;
// Have we found a "mate in x"?
if (limits.mate && rootMoves[0].score == rootMoves[0].uciScore
&& ((rootMoves[0].score >= VALUE_MATE_IN_MAX_PLY
&& VALUE_MATE - rootMoves[0].score <= 2 * limits.mate)
|| (rootMoves[0].score != -VALUE_INFINITE
&& rootMoves[0].score <= VALUE_MATED_IN_MAX_PLY
&& VALUE_MATE + rootMoves[0].score <= 2 * limits.mate)))
threads.stop = true;
// If the skill level is enabled and time is up, pick a sub-optimal best move
if (skill.enabled() && skill.time_to_pick(rootDepth))
skill.pick_best(rootMoves, multiPV);
// Use part of the gained time from a previous stable move for the current move
for (auto&& th : threads)
{
totBestMoveChanges += th->worker->bestMoveChanges;
th->worker->bestMoveChanges = 0;
}
// Do we have time for the next iteration? Can we stop searching now?
if (limits.use_time_management() && !threads.stop && !mainThread->stopOnPonderhit)
{
int nodesEffort = rootMoves[0].effort * 100 / std::max(size_t(1), size_t(nodes));
double fallingEval = (1067 + 223 * (mainThread->bestPreviousAverageScore - bestValue)
+ 97 * (mainThread->iterValue[iterIdx] - bestValue))
/ 10000.0;
fallingEval = std::clamp(fallingEval, 0.580, 1.667);
// If the bestMove is stable over several iterations, reduce time accordingly
timeReduction = lastBestMoveDepth + 8 < completedDepth ? 1.495 : 0.687;
double reduction = (1.48 + mainThread->previousTimeReduction) / (2.17 * timeReduction);
double bestMoveInstability = 1 + 1.88 * totBestMoveChanges / threads.size();
int el = std::clamp((bestValue + 750) / 150, 0, 9);
double recapture = limits.capSq == rootMoves[0].pv[0].to_sq() ? 0.955 : 1.005;
double totalTime = mainThread->tm.optimum() * fallingEval * reduction
* bestMoveInstability * EvalLevel[el] * recapture;
// Cap used time in case of a single legal move for a better viewer experience
if (rootMoves.size() == 1)
totalTime = std::min(500.0, totalTime);
auto elapsedTime = elapsed();
if (completedDepth >= 10 && nodesEffort >= 97 && elapsedTime > totalTime * 0.739
&& !mainThread->ponder)
threads.stop = true;
// Stop the search if we have exceeded the totalTime
if (elapsedTime > totalTime)
{
// If we are allowed to ponder do not stop the search now but
// keep pondering until the GUI sends "ponderhit" or "stop".
if (mainThread->ponder)
mainThread->stopOnPonderhit = true;
else
threads.stop = true;
}
else
threads.increaseDepth = mainThread->ponder || elapsedTime <= totalTime * 0.506;
}
mainThread->iterValue[iterIdx] = bestValue;
iterIdx = (iterIdx + 1) & 3;
}
if (!mainThread)
return;
mainThread->previousTimeReduction = timeReduction;
// If the skill level is enabled, swap the best PV line with the sub-optimal one
if (skill.enabled())
std::swap(rootMoves[0],
*std::find(rootMoves.begin(), rootMoves.end(),
skill.best ? skill.best : skill.pick_best(rootMoves, multiPV)));
}
void Search::Worker::clear() {
counterMoves.fill(Move::none());
mainHistory.fill(0);
captureHistory.fill(0);
pawnHistory.fill(-1193);
correctionHistory.fill(0);
for (bool inCheck : {false, true})
for (StatsType c : {NoCaptures, Captures})
for (auto& to : continuationHistory[inCheck][c])
for (auto& h : to)
h->fill(-56);
for (size_t i = 1; i < reductions.size(); ++i)
reductions[i] = int((19.26 + std::log(size_t(options["Threads"])) / 2) * std::log(i));
refreshTable.clear(networks[numaAccessToken]);
}
// Main search function for both PV and non-PV nodes.
template<NodeType nodeType>
Value Search::Worker::search(
Position& pos, Stack* ss, Value alpha, Value beta, Depth depth, bool cutNode) {
constexpr bool PvNode = nodeType != NonPV;
constexpr bool rootNode = nodeType == Root;
// Dive into quiescence search when the depth reaches zero
if (depth <= 0)
return qsearch < PvNode ? PV : NonPV > (pos, ss, alpha, beta);
// Limit the depth if extensions made it too large
depth = std::min(depth, MAX_PLY - 1);
// Check if we have an upcoming move that draws by repetition, or
// if the opponent had an alternative move earlier to this position.
if (!rootNode && alpha < VALUE_DRAW && pos.has_game_cycle(ss->ply))
{
alpha = value_draw(this->nodes);
if (alpha >= beta)
return alpha;
}
assert(-VALUE_INFINITE <= alpha && alpha < beta && beta <= VALUE_INFINITE);
assert(PvNode || (alpha == beta - 1));
assert(0 < depth && depth < MAX_PLY);
assert(!(PvNode && cutNode));
Move pv[MAX_PLY + 1], capturesSearched[32], quietsSearched[32];
StateInfo st;
ASSERT_ALIGNED(&st, Eval::NNUE::CacheLineSize);
Key posKey;
Move move, excludedMove, bestMove;
Depth extension, newDepth;
Value bestValue, value, eval, maxValue, probCutBeta, singularValue;
bool givesCheck, improving, priorCapture, opponentWorsening;
bool capture, moveCountPruning, ttCapture;
Piece movedPiece;
int moveCount, captureCount, quietCount;
Bound singularBound;
// Step 1. Initialize node
Worker* thisThread = this;
ss->inCheck = pos.checkers();
priorCapture = pos.captured_piece();
Color us = pos.side_to_move();
moveCount = captureCount = quietCount = ss->moveCount = 0;
bestValue = -VALUE_INFINITE;
maxValue = VALUE_INFINITE;
// Check for the available remaining time
if (is_mainthread())
main_manager()->check_time(*thisThread);
// Used to send selDepth info to GUI (selDepth counts from 1, ply from 0)
if (PvNode && thisThread->selDepth < ss->ply + 1)
thisThread->selDepth = ss->ply + 1;
if (!rootNode)
{
// Step 2. Check for aborted search and immediate draw
if (threads.stop.load(std::memory_order_relaxed) || pos.is_draw(ss->ply)
|| ss->ply >= MAX_PLY)
return (ss->ply >= MAX_PLY && !ss->inCheck)
? evaluate(networks[numaAccessToken], pos, refreshTable,
thisThread->optimism[us])
: value_draw(thisThread->nodes);
// 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
// a shorter mate was found upward in the tree then there is no need to search
// because we will never beat the current alpha. Same logic but with reversed
// signs apply also in the opposite condition of being mated instead of giving
// mate. In this case, return a fail-high score.
alpha = std::max(mated_in(ss->ply), alpha);
beta = std::min(mate_in(ss->ply + 1), beta);
if (alpha >= beta)
return alpha;
}
assert(0 <= ss->ply && ss->ply < MAX_PLY);
bestMove = Move::none();
(ss + 2)->killers[0] = (ss + 2)->killers[1] = Move::none();
(ss + 2)->cutoffCnt = 0;
Square prevSq = ((ss - 1)->currentMove).is_ok() ? ((ss - 1)->currentMove).to_sq() : SQ_NONE;
ss->statScore = 0;
// Step 4. Transposition table lookup.
excludedMove = ss->excludedMove;
posKey = pos.key();
auto [ttHit, ttData, ttWriter] = tt.probe(posKey);
// Need further processing of the saved data
ss->ttHit = ttHit;
ttData.move = rootNode ? thisThread->rootMoves[thisThread->pvIdx].pv[0]
: ttHit ? ttData.move
: Move::none();
ttData.value = ttHit ? value_from_tt(ttData.value, ss->ply, pos.rule50_count()) : VALUE_NONE;
ss->ttPv = excludedMove ? ss->ttPv : PvNode || (ttHit && ttData.is_pv);
ttCapture = ttData.move && pos.capture_stage(ttData.move);
// At this point, if excluded, skip straight to step 6, static eval. However,
// to save indentation, we list the condition in all code between here and there.
// At non-PV nodes we check for an early TT cutoff
if (!PvNode && !excludedMove && ttData.depth > depth - (ttData.value <= beta)
&& ttData.value != VALUE_NONE // Can happen when !ttHit or when access race in probe()
&& (ttData.bound & (ttData.value >= beta ? BOUND_LOWER : BOUND_UPPER)))
{
// If ttMove is quiet, update move sorting heuristics on TT hit (~2 Elo)
if (ttData.move && ttData.value >= beta)
{
// Bonus for a quiet ttMove that fails high (~2 Elo)
if (!ttCapture)
update_quiet_stats(pos, ss, *this, ttData.move, stat_bonus(depth));
// Extra penalty for early quiet moves of
// the previous ply (~1 Elo on STC, ~2 Elo on LTC)
if (prevSq != SQ_NONE && (ss - 1)->moveCount <= 2 && !priorCapture)
update_continuation_histories(ss - 1, pos.piece_on(prevSq), prevSq,
-stat_malus(depth + 1));
}
// Partial workaround for the graph history interaction problem
// For high rule50 counts don't produce transposition table cutoffs.
if (pos.rule50_count() < 90)
return ttData.value;
}
// Step 5. Tablebases probe
if (!rootNode && !excludedMove && tbConfig.cardinality)
{
int piecesCount = pos.count<ALL_PIECES>();
if (piecesCount <= tbConfig.cardinality
&& (piecesCount < tbConfig.cardinality || depth >= tbConfig.probeDepth)
&& pos.rule50_count() == 0 && !pos.can_castle(ANY_CASTLING))
{
TB::ProbeState err;
TB::WDLScore wdl = Tablebases::probe_wdl(pos, &err);
// Force check of time on the next occasion
if (is_mainthread())
main_manager()->callsCnt = 0;
if (err != TB::ProbeState::FAIL)
{
thisThread->tbHits.fetch_add(1, std::memory_order_relaxed);
int drawScore = tbConfig.useRule50 ? 1 : 0;
Value tbValue = VALUE_TB - ss->ply;
// use the range VALUE_TB to VALUE_TB_WIN_IN_MAX_PLY to score
value = wdl < -drawScore ? -tbValue
: wdl > drawScore ? tbValue
: VALUE_DRAW + 2 * wdl * drawScore;
Bound b = wdl < -drawScore ? BOUND_UPPER
: wdl > drawScore ? BOUND_LOWER
: BOUND_EXACT;
if (b == BOUND_EXACT || (b == BOUND_LOWER ? value >= beta : value <= alpha))
{
ttWriter.write(posKey, value_to_tt(value, ss->ply), ss->ttPv, b,
std::min(MAX_PLY - 1, depth + 6), Move::none(), VALUE_NONE,
tt.generation());
return value;
}
if (PvNode)
{
if (b == BOUND_LOWER)
bestValue = value, alpha = std::max(alpha, bestValue);
else
maxValue = value;
}
}
}
}
// Step 6. Static evaluation of the position
Value unadjustedStaticEval = VALUE_NONE;
if (ss->inCheck)
{
// Skip early pruning when in check
ss->staticEval = eval = VALUE_NONE;
improving = false;
goto moves_loop;
}
else if (excludedMove)
{
// Providing the hint that this node's accumulator will be used often
// brings significant Elo gain (~13 Elo).
Eval::NNUE::hint_common_parent_position(pos, networks[numaAccessToken], refreshTable);
unadjustedStaticEval = eval = ss->staticEval;
}
else if (ss->ttHit)
{
// Never assume anything about values stored in TT
unadjustedStaticEval = ttData.eval;
if (unadjustedStaticEval == VALUE_NONE)
unadjustedStaticEval =
evaluate(networks[numaAccessToken], pos, refreshTable, thisThread->optimism[us]);
else if (PvNode)
Eval::NNUE::hint_common_parent_position(pos, networks[numaAccessToken], refreshTable);
ss->staticEval = eval = to_corrected_static_eval(unadjustedStaticEval, *thisThread, pos);
// ttValue can be used as a better position evaluation (~7 Elo)
if (ttData.value != VALUE_NONE
&& (ttData.bound & (ttData.value > eval ? BOUND_LOWER : BOUND_UPPER)))
eval = ttData.value;
}
else
{
unadjustedStaticEval =
evaluate(networks[numaAccessToken], pos, refreshTable, thisThread->optimism[us]);
ss->staticEval = eval = to_corrected_static_eval(unadjustedStaticEval, *thisThread, pos);
// Static evaluation is saved as it was before adjustment by correction history
ttWriter.write(posKey, VALUE_NONE, ss->ttPv, BOUND_NONE, DEPTH_UNSEARCHED, Move::none(),
unadjustedStaticEval, tt.generation());
}
// Use static evaluation difference to improve quiet move ordering (~9 Elo)
if (((ss - 1)->currentMove).is_ok() && !(ss - 1)->inCheck && !priorCapture)
{
int bonus = std::clamp(-10 * int((ss - 1)->staticEval + ss->staticEval), -1590, 1371) + 800;
thisThread->mainHistory[~us][((ss - 1)->currentMove).from_to()] << bonus;
if (type_of(pos.piece_on(prevSq)) != PAWN && ((ss - 1)->currentMove).type_of() != PROMOTION)
thisThread->pawnHistory[pawn_structure_index(pos)][pos.piece_on(prevSq)][prevSq]
<< bonus / 2;
}
// Set up the improving flag, which is true if current static evaluation is
// bigger than the previous static evaluation at our turn (if we were in
// check at our previous move we look at static evaluation at move prior to it
// and if we were in check at move prior to it flag is set to true) and is
// false otherwise. The improving flag is used in various pruning heuristics.
improving = (ss - 2)->staticEval != VALUE_NONE
? ss->staticEval > (ss - 2)->staticEval
: (ss - 4)->staticEval != VALUE_NONE && ss->staticEval > (ss - 4)->staticEval;
opponentWorsening = ss->staticEval + (ss - 1)->staticEval > 2;
// Step 7. Razoring (~1 Elo)
// If eval is really low check with qsearch if it can exceed alpha, if it can't,
// return a fail low.
if (eval < alpha - 512 - 293 * depth * depth)
{
value = qsearch<NonPV>(pos, ss, alpha - 1, alpha);
if (value < alpha && std::abs(value) < VALUE_TB_WIN_IN_MAX_PLY)
return value;
}
// Step 8. Futility pruning: child node (~40 Elo)
// The depth condition is important for mate finding.
if (!ss->ttPv && depth < 13
&& eval - futility_margin(depth, cutNode && !ss->ttHit, improving, opponentWorsening)
- (ss - 1)->statScore / 263
>= beta
&& eval >= beta && (!ttData.move || ttCapture) && beta > VALUE_TB_LOSS_IN_MAX_PLY
&& eval < VALUE_TB_WIN_IN_MAX_PLY)
return beta + (eval - beta) / 3;
// Step 9. Null move search with verification search (~35 Elo)
if (!PvNode && (ss - 1)->currentMove != Move::null() && (ss - 1)->statScore < 14369
&& eval >= beta && ss->staticEval >= beta - 21 * depth + 393 && !excludedMove
&& pos.non_pawn_material(us) && ss->ply >= thisThread->nmpMinPly
&& beta > VALUE_TB_LOSS_IN_MAX_PLY)
{
assert(eval - beta >= 0);
// Null move dynamic reduction based on depth and eval
Depth R = std::min(int(eval - beta) / 197, 6) + depth / 3 + 5;
ss->currentMove = Move::null();
ss->continuationHistory = &thisThread->continuationHistory[0][0][NO_PIECE][0];
pos.do_null_move(st, tt);
Value nullValue = -search<NonPV>(pos, ss + 1, -beta, -beta + 1, depth - R, !cutNode);
pos.undo_null_move();
// Do not return unproven mate or TB scores
if (nullValue >= beta && nullValue < VALUE_TB_WIN_IN_MAX_PLY)
{
if (thisThread->nmpMinPly || depth < 16)
return nullValue;
assert(!thisThread->nmpMinPly); // Recursive verification is not allowed
// Do verification search at high depths, with null move pruning disabled
// until ply exceeds nmpMinPly.
thisThread->nmpMinPly = ss->ply + 3 * (depth - R) / 4;
Value v = search<NonPV>(pos, ss, beta - 1, beta, depth - R, false);
thisThread->nmpMinPly = 0;
if (v >= beta)
return nullValue;
}
}
// Step 10. Internal iterative reductions (~9 Elo)
// For PV nodes without a ttMove, we decrease depth.
// Additionally, if the current position is found in the TT
// and the stored depth in the TT is greater than or equal to
// current search depth, we decrease search depth even further.
if (PvNode && !ttData.move)
depth -= 3 + (ss->ttHit && ttData.depth >= depth);
// Use qsearch if depth <= 0.
if (depth <= 0)
return qsearch<PV>(pos, ss, alpha, beta);
// For cutNodes, if depth is high enough, decrease depth by 2 if there is no ttMove, or
// by 1 if there is a ttMove with an upper bound.
if (cutNode && depth >= 8 && (!ttData.move || ttData.bound == BOUND_UPPER))
depth -= 1 + !ttData.move;
// Step 11. ProbCut (~10 Elo)
// If we have a good enough capture (or queen promotion) and a reduced search returns a value
// much above beta, we can (almost) safely prune the previous move.
probCutBeta = beta + 177 - 57 * improving;
if (
!PvNode && depth > 3
&& std::abs(beta) < VALUE_TB_WIN_IN_MAX_PLY
// If value from transposition table is lower than probCutBeta, don't attempt probCut
// there and in further interactions with transposition table cutoff depth is set to depth - 3
// because probCut search has depth set to depth - 4 but we also do a move before it
// So effective depth is equal to depth - 3
&& !(ttData.depth >= depth - 3 && ttData.value != VALUE_NONE && ttData.value < probCutBeta))
{
assert(probCutBeta < VALUE_INFINITE && probCutBeta > beta);
MovePicker mp(pos, ttData.move, probCutBeta - ss->staticEval, &thisThread->captureHistory);
while ((move = mp.next_move()) != Move::none())
if (move != excludedMove && pos.legal(move))
{
assert(pos.capture_stage(move));
// Prefetch the TT entry for the resulting position
prefetch(tt.first_entry(pos.key_after(move)));
ss->currentMove = move;
ss->continuationHistory =
&this
->continuationHistory[ss->inCheck][true][pos.moved_piece(move)][move.to_sq()];
thisThread->nodes.fetch_add(1, std::memory_order_relaxed);
pos.do_move(move, st);
// Perform a preliminary qsearch to verify that the move holds
value = -qsearch<NonPV>(pos, ss + 1, -probCutBeta, -probCutBeta + 1);
// If the qsearch held, perform the regular search
if (value >= probCutBeta)
value = -search<NonPV>(pos, ss + 1, -probCutBeta, -probCutBeta + 1, depth - 4,
!cutNode);
pos.undo_move(move);
if (value >= probCutBeta)
{
// Save ProbCut data into transposition table
ttWriter.write(posKey, value_to_tt(value, ss->ply), ss->ttPv, BOUND_LOWER,
depth - 3, move, unadjustedStaticEval, tt.generation());
return std::abs(value) < VALUE_TB_WIN_IN_MAX_PLY ? value - (probCutBeta - beta)
: value;
}
}
Eval::NNUE::hint_common_parent_position(pos, networks[numaAccessToken], refreshTable);
}
moves_loop: // When in check, search starts here
// Step 12. A small Probcut idea, when we are in check (~4 Elo)
probCutBeta = beta + 388;
if (ss->inCheck && !PvNode && ttCapture && (ttData.bound & BOUND_LOWER)
&& ttData.depth >= depth - 4 && ttData.value >= probCutBeta
&& std::abs(ttData.value) < VALUE_TB_WIN_IN_MAX_PLY
&& std::abs(beta) < VALUE_TB_WIN_IN_MAX_PLY)
return probCutBeta;
const PieceToHistory* contHist[] = {(ss - 1)->continuationHistory,
(ss - 2)->continuationHistory,
(ss - 3)->continuationHistory,
(ss - 4)->continuationHistory,
nullptr,
(ss - 6)->continuationHistory};
Move countermove =
prevSq != SQ_NONE ? thisThread->counterMoves[pos.piece_on(prevSq)][prevSq] : Move::none();
MovePicker mp(pos, ttData.move, depth, &thisThread->mainHistory, &thisThread->captureHistory,
contHist, &thisThread->pawnHistory, countermove, ss->killers);
value = bestValue;
moveCountPruning = false;
singularValue = VALUE_INFINITE;
singularBound = BOUND_NONE;
// Step 13. Loop through all pseudo-legal moves until no moves remain
// or a beta cutoff occurs.
while ((move = mp.next_move(moveCountPruning)) != Move::none())
{
assert(move.is_ok());
if (move == excludedMove)
continue;
// Check for legality
if (!pos.legal(move))
continue;
// At root obey the "searchmoves" option and skip moves not listed in Root
// Move List. In MultiPV mode we also skip PV moves that have been already
// searched and those of lower "TB rank" if we are in a TB root position.
if (rootNode
&& !std::count(thisThread->rootMoves.begin() + thisThread->pvIdx,
thisThread->rootMoves.begin() + thisThread->pvLast, move))
continue;
ss->moveCount = ++moveCount;
if (rootNode && is_mainthread() && elapsed_time() > 3000)
{
main_manager()->updates.onIter(
{depth, UCIEngine::move(move, pos.is_chess960()), moveCount + thisThread->pvIdx});
}
if (PvNode)
(ss + 1)->pv = nullptr;
extension = 0;
capture = pos.capture_stage(move);
movedPiece = pos.moved_piece(move);
givesCheck = pos.gives_check(move);
// Calculate new depth for this move
newDepth = depth - 1;
int delta = beta - alpha;
Depth r = reduction(improving, depth, moveCount, delta);
// Step 14. Pruning at shallow depth (~120 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 (~8 Elo)
moveCountPruning =
moveCount >= futility_move_count(improving, depth)
- (singularBound == BOUND_UPPER && singularValue < alpha - 50);
// Reduced depth of the next LMR search
int lmrDepth = newDepth - r;
if (capture || givesCheck)
{
Piece capturedPiece = pos.piece_on(move.to_sq());
int captHist =
thisThread->captureHistory[movedPiece][move.to_sq()][type_of(capturedPiece)];
// Futility pruning for captures (~2 Elo)
if (!givesCheck && lmrDepth < 7 && !ss->inCheck)
{
Value futilityValue = ss->staticEval + 287 + 248 * lmrDepth
+ PieceValue[capturedPiece] + captHist / 7;
if (futilityValue <= alpha)
continue;
}
// SEE based pruning for captures and checks (~11 Elo)
int seeHist = std::clamp(captHist / 32, -180 * depth, 163 * depth);
if (!pos.see_ge(move, -160 * depth - seeHist))
continue;
}
else
{
int history =
(*contHist[0])[movedPiece][move.to_sq()]
+ (*contHist[1])[movedPiece][move.to_sq()]
+ thisThread->pawnHistory[pawn_structure_index(pos)][movedPiece][move.to_sq()];
// Continuation history based pruning (~2 Elo)
if (lmrDepth < 6 && history < -4151 * depth)
continue;
history += 2 * thisThread->mainHistory[us][move.from_to()];
lmrDepth += history / 3678;
Value futilityValue =
ss->staticEval + (bestValue < ss->staticEval - 51 ? 138 : 54) + 140 * lmrDepth;
// Futility pruning: parent node (~13 Elo)
if (!ss->inCheck && lmrDepth < 12 && futilityValue <= alpha)
{
if (bestValue <= futilityValue && std::abs(bestValue) < VALUE_TB_WIN_IN_MAX_PLY
&& futilityValue < VALUE_TB_WIN_IN_MAX_PLY)
bestValue = (bestValue + futilityValue * 3) / 4;
continue;
}
lmrDepth = std::max(lmrDepth, 0);
// Prune moves with negative SEE (~4 Elo)
if (!pos.see_ge(move, -24 * lmrDepth * lmrDepth))
continue;
}
}
// Step 15. Extensions (~100 Elo)
// We take care to not overdo to avoid search getting stuck.
if (ss->ply < thisThread->rootDepth * 2)
{
// Singular extension search (~94 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 the position excluding the ttMove and if the result
// is lower than ttValue minus a margin, then we will extend the ttMove.
// Recursive singular search is avoided.
// Note: the depth margin and singularBeta margin are known for having non-linear
// scaling. Their values are optimized to time controls of 180+1.8 and longer
// so changing them requires tests at these types of time controls.
// Generally, higher singularBeta (i.e closer to ttValue) and lower extension
// margins scale well.
if (!rootNode && move == ttData.move && !excludedMove
&& depth >= 4 - (thisThread->completedDepth > 35) + ss->ttPv
&& std::abs(ttData.value) < VALUE_TB_WIN_IN_MAX_PLY && (ttData.bound & BOUND_LOWER)
&& ttData.depth >= depth - 3)
{
Value singularBeta = ttData.value - (52 + 80 * (ss->ttPv && !PvNode)) * depth / 64;
Depth singularDepth = newDepth / 2;
ss->excludedMove = move;
value = singularValue =
search<NonPV>(pos, ss, singularBeta - 1, singularBeta, singularDepth, cutNode);
singularBound = singularValue >= singularBeta ? BOUND_LOWER : BOUND_UPPER;
ss->excludedMove = Move::none();
if (value < singularBeta)
{
int doubleMargin = 290 * PvNode - 200 * !ttCapture;
int tripleMargin = 107 + 247 * PvNode - 278 * !ttCapture + 99 * ss->ttPv;
extension = 1 + (value < singularBeta - doubleMargin)
+ (value < singularBeta - tripleMargin);
depth += ((!PvNode) && (depth < 18));
}
// Multi-cut pruning
// Our ttMove is assumed to fail high based on the bound of the TT entry,
// and if after excluding the ttMove with a reduced search we fail high over the original beta,
// we assume this expected cut-node is not singular (multiple moves fail high),
// and we can prune the whole subtree by returning a softbound.
else if (value >= beta && std::abs(value) < VALUE_TB_WIN_IN_MAX_PLY)
return value;
// Negative extensions
// If other moves failed high over (ttValue - margin) without the ttMove on a reduced search,
// but we cannot do multi-cut because (ttValue - margin) is lower than the original beta,
// we do not know if the ttMove is singular or can do a multi-cut,
// so we reduce the ttMove in favor of other moves based on some conditions:
// If the ttMove is assumed to fail high over current beta (~7 Elo)
else if (ttData.value >= beta)
extension = -3;
// If we are on a cutNode but the ttMove is not assumed to fail high over current beta (~1 Elo)
else if (cutNode)
extension = -2;
}
// Extension for capturing the previous moved piece (~0 Elo on STC, ~1 Elo on LTC)
else if (PvNode && move.to_sq() == prevSq
&& thisThread->captureHistory[movedPiece][move.to_sq()]
[type_of(pos.piece_on(move.to_sq()))]
> 3922)
extension = 1;
}
// Add extension to new depth
newDepth += extension;
// Speculative prefetch as early as possible
prefetch(tt.first_entry(pos.key_after(move)));
// Update the current move (this must be done after singular extension search)
ss->currentMove = move;
ss->continuationHistory =
&thisThread->continuationHistory[ss->inCheck][capture][movedPiece][move.to_sq()];
uint64_t nodeCount = rootNode ? uint64_t(nodes) : 0;
// Step 16. Make the move
thisThread->nodes.fetch_add(1, std::memory_order_relaxed);
pos.do_move(move, st, givesCheck);
// These reduction adjustments have proven non-linear scaling.
// They are optimized to time controls of 180 + 1.8 and longer so
// changing them or adding conditions that are similar
// requires tests at these types of time controls.
// Decrease reduction if position is or has been on the PV (~7 Elo)
if (ss->ttPv)
r -= 1 + (ttData.value > alpha) + (ttData.depth >= depth)
- (PvNode && ttData.value < alpha && ttData.depth >= depth);
// Decrease reduction for PvNodes (~0 Elo on STC, ~2 Elo on LTC)
if (PvNode)
r--;
// These reduction adjustments have no proven non-linear scaling.
// Increase reduction for cut nodes (~4 Elo)
if (cutNode)
r += 2 - (ttData.depth >= depth && ss->ttPv)
+ (!ss->ttPv && move != ttData.move && move != ss->killers[0]);
// Increase reduction if ttMove is a capture (~3 Elo)
if (ttCapture)
r++;
// Increase reduction if next ply has a lot of fail high (~5 Elo)
if ((ss + 1)->cutoffCnt > 3)
r++;
// For first picked move (ttMove) reduce reduction
// but never allow it to go below 0 (~3 Elo)
else if (move == ttData.move)
r = std::max(0, r - 2);
ss->statScore = 2 * thisThread->mainHistory[us][move.from_to()]
+ (*contHist[0])[movedPiece][move.to_sq()]
+ (*contHist[1])[movedPiece][move.to_sq()] - 4747;
// Decrease/increase reduction for moves with a good/bad history (~8 Elo)
r -= ss->statScore / 11125;
// Step 17. Late moves reduction / extension (LMR, ~117 Elo)
if (depth >= 2 && moveCount > 1 + rootNode)
{
// In general we want to cap the LMR depth search at newDepth, but when
// reduction is negative, we allow this move a limited search extension
// beyond the first move depth.
// To prevent problems when the max value is less than the min value,
// std::clamp has been replaced by a more robust implementation.
Depth d = std::max(1, std::min(newDepth - r, newDepth + 1));
value = -search<NonPV>(pos, ss + 1, -(alpha + 1), -alpha, d, true);
// Do a full-depth search when reduced LMR search fails high
if (value > alpha && d < newDepth)
{
// Adjust full-depth search based on LMR results - if the result
// was good enough search deeper, if it was bad enough search shallower.
const bool doDeeperSearch = value > (bestValue + 35 + 2 * newDepth); // (~1 Elo)
const bool doShallowerSearch = value < bestValue + newDepth; // (~2 Elo)
newDepth += doDeeperSearch - doShallowerSearch;
if (newDepth > d)
value = -search<NonPV>(pos, ss + 1, -(alpha + 1), -alpha, newDepth, !cutNode);
// Post LMR continuation history updates (~1 Elo)
int bonus = value <= alpha ? -stat_malus(newDepth)
: value >= beta ? stat_bonus(newDepth)
: 0;
update_continuation_histories(ss, movedPiece, move.to_sq(), bonus);
}
}
// Step 18. Full-depth search when LMR is skipped
else if (!PvNode || moveCount > 1)
{
// Increase reduction if ttMove is not present (~6 Elo)
if (!ttData.move)
r += 2;
// Note that if expected reduction is high, we reduce search depth by 1 here (~9 Elo)
value = -search<NonPV>(pos, ss + 1, -(alpha + 1), -alpha, newDepth - (r > 3), !cutNode);
}
// For PV nodes only, do a full PV search on the first move or after a fail high,
// otherwise let the parent node fail low with value <= alpha and try another move.
if (PvNode && (moveCount == 1 || value > alpha))
{
(ss + 1)->pv = pv;
(ss + 1)->pv[0] = Move::none();
value = -search<PV>(pos, ss + 1, -beta, -alpha, newDepth, false);
}
// Step 19. Undo move
pos.undo_move(move);
assert(value > -VALUE_INFINITE && value < VALUE_INFINITE);
// Step 20. Check for a new best move
// Finished searching the move. If a stop occurred, the return value of
// the search cannot be trusted, and we return immediately without
// updating best move, PV and TT.
if (threads.stop.load(std::memory_order_relaxed))
return VALUE_ZERO;
if (rootNode)
{
RootMove& rm =
*std::find(thisThread->rootMoves.begin(), thisThread->rootMoves.end(), move);
rm.effort += nodes - nodeCount;
rm.averageScore =
rm.averageScore != -VALUE_INFINITE ? (2 * value + rm.averageScore) / 3 : value;
// PV move or new best move?
if (moveCount == 1 || value > alpha)
{
rm.score = rm.uciScore = value;
rm.selDepth = thisThread->selDepth;
rm.scoreLowerbound = rm.scoreUpperbound = false;
if (value >= beta)
{
rm.scoreLowerbound = true;
rm.uciScore = beta;
}
else if (value <= alpha)
{
rm.scoreUpperbound = true;
rm.uciScore = alpha;
}
rm.pv.resize(1);
assert((ss + 1)->pv);
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. In MultiPV mode,
// we must take care to only do this for the first PV line.
if (moveCount > 1 && !thisThread->pvIdx)
++thisThread->bestMoveChanges;
}
else
// All other moves but the PV, are set to the lowest value: this
// is not a problem when sorting because the sort is stable and the
// move position in the list is preserved - just the PV is pushed up.
rm.score = -VALUE_INFINITE;
}
// In case we have an alternative move equal in eval to the current bestmove,
// promote it to bestmove by pretending it just exceeds alpha (but not beta).
int inc = (value == bestValue && (int(nodes) & 15) == 0
&& ss->ply + 2 + ss->ply / 32 >= thisThread->rootDepth
&& std::abs(value) + 1 < VALUE_TB_WIN_IN_MAX_PLY);
if (value + inc > bestValue)
{
bestValue = value;
if (value + inc > alpha)
{
bestMove = move;
if (PvNode && !rootNode) // Update pv even in fail-high case
update_pv(ss->pv, move, (ss + 1)->pv);
if (value >= beta)
{
ss->cutoffCnt += 1 + !ttData.move - (extension >= 2);
assert(value >= beta); // Fail high
break;
}
else
{
// Reduce other moves if we have found at least one score improvement (~2 Elo)
if (depth > 2 && depth < 13 && std::abs(value) < VALUE_TB_WIN_IN_MAX_PLY)
depth -= 2;
assert(depth > 0);
alpha = value; // Update alpha! Always alpha < beta
}
}
}
// If the move is worse than some previously searched move,
// remember it, to update its stats later.
if (move != bestMove && moveCount <= 32)
{
if (capture)
capturesSearched[captureCount++] = move;
else
quietsSearched[quietCount++] = move;
}
}
// Step 21. Check for mate and stalemate
// All legal moves have been searched and if there are no legal moves, it
// must be a mate or a stalemate. If we are in a singular extension search then
// return a fail low score.
assert(moveCount || !ss->inCheck || excludedMove || !MoveList<LEGAL>(pos).size());
// Adjust best value for fail high cases at non-pv nodes
if (!PvNode && bestValue >= beta && std::abs(bestValue) < VALUE_TB_WIN_IN_MAX_PLY
&& std::abs(beta) < VALUE_TB_WIN_IN_MAX_PLY && std::abs(alpha) < VALUE_TB_WIN_IN_MAX_PLY)
bestValue = (bestValue * depth + beta) / (depth + 1);
if (!moveCount)
bestValue = excludedMove ? alpha : ss->inCheck ? mated_in(ss->ply) : VALUE_DRAW;
// If there is a move that produces search value greater than alpha we update the stats of searched moves
else if (bestMove)
update_all_stats(pos, ss, *this, bestMove, bestValue, beta, prevSq, quietsSearched,
quietCount, capturesSearched, captureCount, depth);
// Bonus for prior countermove that caused the fail low
else if (!priorCapture && prevSq != SQ_NONE)
{
int bonus = (113 * (depth > 5) + 118 * (PvNode || cutNode) + 119 * ((ss - 1)->moveCount > 8)
+ 64 * (!ss->inCheck && bestValue <= ss->staticEval - 107)
+ 147 * (!(ss - 1)->inCheck && bestValue <= -(ss - 1)->staticEval - 75));
// proportional to "how much damage we have to undo"
if ((ss - 1)->statScore < -8000)
bonus += std::clamp(-(ss - 1)->statScore / 100, 0, 250);
update_continuation_histories(ss - 1, pos.piece_on(prevSq), prevSq,
stat_bonus(depth) * bonus / 100);
thisThread->mainHistory[~us][((ss - 1)->currentMove).from_to()]
<< stat_bonus(depth) * bonus / 200;
if (type_of(pos.piece_on(prevSq)) != PAWN && ((ss - 1)->currentMove).type_of() != PROMOTION)
thisThread->pawnHistory[pawn_structure_index(pos)][pos.piece_on(prevSq)][prevSq]
<< stat_bonus(depth) * bonus / 25;
}
if (PvNode)
bestValue = std::min(bestValue, maxValue);
// If no good move is found and the previous position was ttPv, then the previous
// opponent move is probably good and the new position is added to the search tree. (~7 Elo)
if (bestValue <= alpha)
ss->ttPv = ss->ttPv || ((ss - 1)->ttPv && depth > 3);
// Write gathered information in transposition table
// Static evaluation is saved as it was before correction history
if (!excludedMove && !(rootNode && thisThread->pvIdx))
ttWriter.write(posKey, value_to_tt(bestValue, ss->ply), ss->ttPv,
bestValue >= beta ? BOUND_LOWER
: PvNode && bestMove ? BOUND_EXACT
: BOUND_UPPER,
depth, bestMove, unadjustedStaticEval, tt.generation());
// Adjust correction history
if (!ss->inCheck && (!bestMove || !pos.capture(bestMove))
&& !(bestValue >= beta && bestValue <= ss->staticEval)
&& !(!bestMove && bestValue >= ss->staticEval))
{
auto bonus = std::clamp(int(bestValue - ss->staticEval) * depth / 8,
-CORRECTION_HISTORY_LIMIT / 4, CORRECTION_HISTORY_LIMIT / 4);
thisThread->correctionHistory[us][pawn_structure_index<Correction>(pos)] << bonus;
}
assert(bestValue > -VALUE_INFINITE && bestValue < VALUE_INFINITE);
return bestValue;
}
// Quiescence search function, which is called by the main search function with zero depth, or
// recursively with further decreasing depth per call. With depth <= 0, we "should" be using
// static eval only, but tactical moves may confuse the static eval. To fight this horizon effect,
// we implement this qsearch of tactical moves only.
// See https://www.chessprogramming.org/Horizon_Effect and https://www.chessprogramming.org/Quiescence_Search
// (~155 Elo)
template<NodeType nodeType>
Value Search::Worker::qsearch(Position& pos, Stack* ss, Value alpha, Value beta, Depth depth) {
static_assert(nodeType != Root);
constexpr bool PvNode = nodeType == PV;
assert(alpha >= -VALUE_INFINITE && alpha < beta && beta <= VALUE_INFINITE);
assert(PvNode || (alpha == beta - 1));
assert(depth <= 0);
// Check if we have an upcoming move that draws by repetition, or if
// the opponent had an alternative move earlier to this position. (~1 Elo)
if (alpha < VALUE_DRAW && pos.has_game_cycle(ss->ply))
{
alpha = value_draw(this->nodes);
if (alpha >= beta)
return alpha;
}
Move pv[MAX_PLY + 1];
StateInfo st;
ASSERT_ALIGNED(&st, Eval::NNUE::CacheLineSize);
Key posKey;
Move move, bestMove;
Value bestValue, value, futilityBase;
bool pvHit, givesCheck, capture;
int moveCount;
Color us = pos.side_to_move();
// Step 1. Initialize node
if (PvNode)
{
(ss + 1)->pv = pv;
ss->pv[0] = Move::none();
}
Worker* thisThread = this;
bestMove = Move::none();
ss->inCheck = pos.checkers();
moveCount = 0;
// Used to send selDepth info to GUI (selDepth counts from 1, ply from 0)
if (PvNode && thisThread->selDepth < ss->ply + 1)
thisThread->selDepth = ss->ply + 1;
// Step 2. Check for an immediate draw or maximum ply reached
if (pos.is_draw(ss->ply) || ss->ply >= MAX_PLY)
return (ss->ply >= MAX_PLY && !ss->inCheck)
? evaluate(networks[numaAccessToken], pos, refreshTable, thisThread->optimism[us])
: VALUE_DRAW;
assert(0 <= ss->ply && ss->ply < MAX_PLY);
// Note that unlike regular search, which stores the literal depth into the TT, from QS we
// only store the current movegen stage as "depth". If in check, we search all evasions and
// thus store DEPTH_QS_CHECKS. (Evasions may be quiet, and _CHECKS includes quiets.)
Depth qsTtDepth = ss->inCheck || depth >= DEPTH_QS_CHECKS ? DEPTH_QS_CHECKS : DEPTH_QS_NORMAL;
// Step 3. Transposition table lookup
posKey = pos.key();
auto [ttHit, ttData, ttWriter] = tt.probe(posKey);
// Need further processing of the saved data
ss->ttHit = ttHit;
ttData.move = ttHit ? ttData.move : Move::none();
ttData.value = ttHit ? value_from_tt(ttData.value, ss->ply, pos.rule50_count()) : VALUE_NONE;
pvHit = ttHit && ttData.is_pv;
// At non-PV nodes we check for an early TT cutoff
if (!PvNode && ttData.depth >= qsTtDepth
&& ttData.value != VALUE_NONE // Can happen when !ttHit or when access race in probe()
&& (ttData.bound & (ttData.value >= beta ? BOUND_LOWER : BOUND_UPPER)))
return ttData.value;
// Step 4. Static evaluation of the position
Value unadjustedStaticEval = VALUE_NONE;
if (ss->inCheck)
bestValue = futilityBase = -VALUE_INFINITE;
else
{
if (ss->ttHit)
{
// Never assume anything about values stored in TT
unadjustedStaticEval = ttData.eval;
if (unadjustedStaticEval == VALUE_NONE)
unadjustedStaticEval =
evaluate(networks[numaAccessToken], pos, refreshTable, thisThread->optimism[us]);
ss->staticEval = bestValue =
to_corrected_static_eval(unadjustedStaticEval, *thisThread, pos);
// ttValue can be used as a better position evaluation (~13 Elo)
if (std::abs(ttData.value) < VALUE_TB_WIN_IN_MAX_PLY
&& (ttData.bound & (ttData.value > bestValue ? BOUND_LOWER : BOUND_UPPER)))
bestValue = ttData.value;
}
else
{
// In case of null move search, use previous static eval with a different sign
unadjustedStaticEval =
(ss - 1)->currentMove != Move::null()
? evaluate(networks[numaAccessToken], pos, refreshTable, thisThread->optimism[us])
: -(ss - 1)->staticEval;
ss->staticEval = bestValue =
to_corrected_static_eval(unadjustedStaticEval, *thisThread, pos);
}
// Stand pat. Return immediately if static value is at least beta
if (bestValue >= beta)
{
if (std::abs(bestValue) < VALUE_TB_WIN_IN_MAX_PLY && !PvNode)
bestValue = (3 * bestValue + beta) / 4;
if (!ss->ttHit)
ttWriter.write(posKey, value_to_tt(bestValue, ss->ply), false, BOUND_LOWER,
DEPTH_UNSEARCHED, Move::none(), unadjustedStaticEval,
tt.generation());
return bestValue;
}
if (bestValue > alpha)
alpha = bestValue;
futilityBase = ss->staticEval + 294;
}
const PieceToHistory* contHist[] = {(ss - 1)->continuationHistory,
(ss - 2)->continuationHistory};
// Initialize a MovePicker object for the current position, and prepare to search the moves.
// We presently use two stages of qs movegen, first captures+checks, then captures only.
// (When in check, we simply search all evasions.)
// (Presently, having the checks stage is worth only 1 Elo, and may be removable in the near future,
// which would result in only a single stage of QS movegen.)
Square prevSq = ((ss - 1)->currentMove).is_ok() ? ((ss - 1)->currentMove).to_sq() : SQ_NONE;
MovePicker mp(pos, ttData.move, depth, &thisThread->mainHistory, &thisThread->captureHistory,
contHist, &thisThread->pawnHistory);
// Step 5. Loop through all pseudo-legal moves until no moves remain or a beta cutoff occurs.
while ((move = mp.next_move()) != Move::none())
{
assert(move.is_ok());
// Check for legality
if (!pos.legal(move))
continue;
givesCheck = pos.gives_check(move);
capture = pos.capture_stage(move);
moveCount++;
// Step 6. Pruning
if (bestValue > VALUE_TB_LOSS_IN_MAX_PLY && pos.non_pawn_material(us))
{
// Futility pruning and moveCount pruning (~10 Elo)
if (!givesCheck && move.to_sq() != prevSq && futilityBase > VALUE_TB_LOSS_IN_MAX_PLY
&& move.type_of() != PROMOTION)
{
if (moveCount > 2)
continue;
Value futilityValue = futilityBase + PieceValue[pos.piece_on(move.to_sq())];
// If static eval + value of piece we are going to capture is much lower
// than alpha we can prune this move. (~2 Elo)
if (futilityValue <= alpha)
{
bestValue = std::max(bestValue, futilityValue);
continue;
}
// If static eval is much lower than alpha and move is not winning material
// we can prune this move. (~2 Elo)
if (futilityBase <= alpha && !pos.see_ge(move, 1))
{
bestValue = std::max(bestValue, futilityBase);
continue;
}
// If static exchange evaluation is much worse than what is needed to not
// fall below alpha we can prune this move.
if (futilityBase > alpha && !pos.see_ge(move, (alpha - futilityBase) * 4))
{
bestValue = alpha;
continue;
}
}
// Continuation history based pruning (~3 Elo)
if (!capture
&& (*contHist[0])[pos.moved_piece(move)][move.to_sq()]
+ (*contHist[1])[pos.moved_piece(move)][move.to_sq()]
+ thisThread->pawnHistory[pawn_structure_index(pos)][pos.moved_piece(move)]
[move.to_sq()]
<= 4452)
continue;
// Do not search moves with bad enough SEE values (~5 Elo)
if (!pos.see_ge(move, -74))
continue;
}
// Speculative prefetch as early as possible
prefetch(tt.first_entry(pos.key_after(move)));
// Update the current move
ss->currentMove = move;
ss->continuationHistory =
&thisThread
->continuationHistory[ss->inCheck][capture][pos.moved_piece(move)][move.to_sq()];
// Step 7. Make and search the move
thisThread->nodes.fetch_add(1, std::memory_order_relaxed);
pos.do_move(move, st, givesCheck);
value = -qsearch<nodeType>(pos, ss + 1, -beta, -alpha, depth - 1);
pos.undo_move(move);
assert(value > -VALUE_INFINITE && value < VALUE_INFINITE);
// Step 8. Check for a new best move
if (value > bestValue)
{
bestValue = value;
if (value > alpha)
{
bestMove = move;
if (PvNode) // Update pv even in fail-high case
update_pv(ss->pv, move, (ss + 1)->pv);
if (value < beta) // Update alpha here!
alpha = value;
else
break; // Fail high
}
}
}
// Step 9. Check for mate
// 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)
{
assert(!MoveList<LEGAL>(pos).size());
return mated_in(ss->ply); // Plies to mate from the root
}
if (std::abs(bestValue) < VALUE_TB_WIN_IN_MAX_PLY && bestValue >= beta)
bestValue = (3 * bestValue + beta) / 4;
// Save gathered info in transposition table
// Static evaluation is saved as it was before adjustment by correction history
ttWriter.write(posKey, value_to_tt(bestValue, ss->ply), pvHit,
bestValue >= beta ? BOUND_LOWER : BOUND_UPPER, qsTtDepth, bestMove,
unadjustedStaticEval, tt.generation());
assert(bestValue > -VALUE_INFINITE && bestValue < VALUE_INFINITE);
return bestValue;
}
Depth Search::Worker::reduction(bool i, Depth d, int mn, int delta) const {
int reductionScale = reductions[d] * reductions[mn];
return (reductionScale + 1236 - delta * 746 / rootDelta) / 1024 + (!i && reductionScale > 1326);
}
// elapsed() returns the time elapsed since the search started. If the
// 'nodestime' option is enabled, it will return the count of nodes searched
// instead. This function is called to check whether the search should be
// stopped based on predefined thresholds like time limits or nodes searched.
//
// elapsed_time() returns the actual time elapsed since the start of the search.
// This function is intended for use only when printing PV outputs, and not used
// for making decisions within the search algorithm itself.
TimePoint Search::Worker::elapsed() const {
return main_manager()->tm.elapsed([this]() { return threads.nodes_searched(); });
}
TimePoint Search::Worker::elapsed_time() const { return main_manager()->tm.elapsed_time(); }
namespace {
// 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.
// The function is called before storing a value in the transposition table.
Value value_to_tt(Value v, int ply) {
assert(v != VALUE_NONE);
return v >= VALUE_TB_WIN_IN_MAX_PLY ? v + ply : v <= VALUE_TB_LOSS_IN_MAX_PLY ? v - ply : v;
}
// 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, to avoid potentially false mate or TB scores related to the 50 moves rule
// and the graph history interaction, we return the highest non-TB score instead.
Value value_from_tt(Value v, int ply, int r50c) {
if (v == VALUE_NONE)
return VALUE_NONE;
// handle TB win or better
if (v >= VALUE_TB_WIN_IN_MAX_PLY)
{
// Downgrade a potentially false mate score
if (v >= VALUE_MATE_IN_MAX_PLY && VALUE_MATE - v > 100 - r50c)
return VALUE_TB_WIN_IN_MAX_PLY - 1;
// Downgrade a potentially false TB score.
if (VALUE_TB - v > 100 - r50c)
return VALUE_TB_WIN_IN_MAX_PLY - 1;
return v - ply;
}
// handle TB loss or worse
if (v <= VALUE_TB_LOSS_IN_MAX_PLY)
{
// Downgrade a potentially false mate score.
if (v <= VALUE_MATED_IN_MAX_PLY && VALUE_MATE + v > 100 - r50c)
return VALUE_TB_LOSS_IN_MAX_PLY + 1;
// Downgrade a potentially false TB score.
if (VALUE_TB + v > 100 - r50c)
return VALUE_TB_LOSS_IN_MAX_PLY + 1;
return v + ply;
}
return v;
}
// Adds current move and appends child pv[]
void update_pv(Move* pv, Move move, const Move* childPv) {
for (*pv++ = move; childPv && *childPv != Move::none();)
*pv++ = *childPv++;
*pv = Move::none();
}
// Updates stats at the end of search() when a bestMove is found
void update_all_stats(const Position& pos,
Stack* ss,
Search::Worker& workerThread,
Move bestMove,
Value bestValue,
Value beta,
Square prevSq,
Move* quietsSearched,
int quietCount,
Move* capturesSearched,
int captureCount,
Depth depth) {
CapturePieceToHistory& captureHistory = workerThread.captureHistory;
Piece moved_piece = pos.moved_piece(bestMove);
PieceType captured;
int quietMoveBonus = stat_bonus(depth + 1);
int quietMoveMalus = stat_malus(depth);
if (!pos.capture_stage(bestMove))
{
int bestMoveBonus = bestValue > beta + 164 ? quietMoveBonus // larger bonus
: stat_bonus(depth); // smaller bonus
update_quiet_stats(pos, ss, workerThread, bestMove, bestMoveBonus);
// Decrease stats for all non-best quiet moves
for (int i = 0; i < quietCount; ++i)
update_quiet_histories(pos, ss, workerThread, quietsSearched[i], -quietMoveMalus);
}
else
{
// Increase stats for the best move in case it was a capture move
captured = type_of(pos.piece_on(bestMove.to_sq()));
captureHistory[moved_piece][bestMove.to_sq()][captured] << quietMoveBonus;
}
// Extra penalty for a quiet early move that was not a TT move or
// main killer move in previous ply when it gets refuted.
if (prevSq != SQ_NONE
&& ((ss - 1)->moveCount == 1 + (ss - 1)->ttHit
|| ((ss - 1)->currentMove == (ss - 1)->killers[0]))
&& !pos.captured_piece())
update_continuation_histories(ss - 1, pos.piece_on(prevSq), prevSq, -quietMoveMalus);
// Decrease stats for all non-best capture moves
for (int i = 0; i < captureCount; ++i)
{
moved_piece = pos.moved_piece(capturesSearched[i]);
captured = type_of(pos.piece_on(capturesSearched[i].to_sq()));
captureHistory[moved_piece][capturesSearched[i].to_sq()][captured] << -quietMoveMalus;
}
}
// Updates histories of the move pairs formed
// by moves at ply -1, -2, -3, -4, and -6 with current move.
void update_continuation_histories(Stack* ss, Piece pc, Square to, int bonus) {
bonus = bonus * 51 / 64;
for (int i : {1, 2, 3, 4, 6})
{
// Only update the first 2 continuation histories if we are in check
if (ss->inCheck && i > 2)
break;
if (((ss - i)->currentMove).is_ok())
(*(ss - i)->continuationHistory)[pc][to] << bonus / (1 + (i == 3));
}
}
// Updates move sorting heuristics
void update_refutations(const Position& pos, Stack* ss, Search::Worker& workerThread, Move move) {
// Update killers
if (ss->killers[0] != move)
{
ss->killers[1] = ss->killers[0];
ss->killers[0] = move;
}
// Update countermove history
if (((ss - 1)->currentMove).is_ok())
{
Square prevSq = ((ss - 1)->currentMove).to_sq();
workerThread.counterMoves[pos.piece_on(prevSq)][prevSq] = move;
}
}
void update_quiet_histories(
const Position& pos, Stack* ss, Search::Worker& workerThread, Move move, int bonus) {
Color us = pos.side_to_move();
workerThread.mainHistory[us][move.from_to()] << bonus;
update_continuation_histories(ss, pos.moved_piece(move), move.to_sq(), bonus);
int pIndex = pawn_structure_index(pos);
workerThread.pawnHistory[pIndex][pos.moved_piece(move)][move.to_sq()] << bonus / 2;
}
// Updates move sorting heuristics
void update_quiet_stats(
const Position& pos, Stack* ss, Search::Worker& workerThread, Move move, int bonus) {
update_refutations(pos, ss, workerThread, move);
update_quiet_histories(pos, ss, workerThread, move, bonus);
}
}
// When playing with strength handicap, choose the best move among a set of RootMoves
// using a statistical rule dependent on 'level'. Idea by Heinz van Saanen.
Move Skill::pick_best(const RootMoves& rootMoves, size_t multiPV) {
static PRNG rng(now()); // PRNG sequence should be non-deterministic
// RootMoves are already sorted by score in descending order
Value topScore = rootMoves[0].score;
int delta = std::min(topScore - rootMoves[multiPV - 1].score, int(PawnValue));
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
// random. Then we choose the move with the resulting highest score.
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>() % int(weakness)))
/ 128;
if (rootMoves[i].score + push >= maxScore)
{
maxScore = rootMoves[i].score + push;
best = rootMoves[i].pv[0];
}
}
return best;
}
// Used to print debug info and, more importantly,
// to detect when we are out of available time and thus stop the search.
void SearchManager::check_time(Search::Worker& worker) {
if (--callsCnt > 0)
return;
// When using nodes, ensure checking rate is not lower than 0.1% of nodes
callsCnt = worker.limits.nodes ? std::min(512, int(worker.limits.nodes / 1024)) : 512;
static TimePoint lastInfoTime = now();
TimePoint elapsed = tm.elapsed([&worker]() { return worker.threads.nodes_searched(); });
TimePoint tick = worker.limits.startTime + elapsed;
if (tick - lastInfoTime >= 1000)
{
lastInfoTime = tick;
dbg_print();
}
// We should not stop pondering until told so by the GUI
if (ponder)
return;
if (
// Later we rely on the fact that we can at least use the mainthread previous
// root-search score and PV in a multithreaded environment to prove mated-in scores.
worker.completedDepth >= 1
&& ((worker.limits.use_time_management() && (elapsed > tm.maximum() || stopOnPonderhit))
|| (worker.limits.movetime && elapsed >= worker.limits.movetime)
|| (worker.limits.nodes && worker.threads.nodes_searched() >= worker.limits.nodes)))
worker.threads.stop = worker.threads.abortedSearch = true;
}
void SearchManager::pv(const Search::Worker& worker,
const ThreadPool& threads,
const TranspositionTable& tt,
Depth depth) const {
const auto nodes = threads.nodes_searched();
const auto& rootMoves = worker.rootMoves;
const auto& pos = worker.rootPos;
size_t pvIdx = worker.pvIdx;
TimePoint time = tm.elapsed_time() + 1;
size_t multiPV = std::min(size_t(worker.options["MultiPV"]), rootMoves.size());
uint64_t tbHits = threads.tb_hits() + (worker.tbConfig.rootInTB ? rootMoves.size() : 0);
for (size_t i = 0; i < multiPV; ++i)
{
bool updated = rootMoves[i].score != -VALUE_INFINITE;
if (depth == 1 && !updated && i > 0)
continue;
Depth d = updated ? depth : std::max(1, depth - 1);
Value v = updated ? rootMoves[i].uciScore : rootMoves[i].previousScore;
if (v == -VALUE_INFINITE)
v = VALUE_ZERO;
bool tb = worker.tbConfig.rootInTB && std::abs(v) <= VALUE_TB;
v = tb ? rootMoves[i].tbScore : v;
std::string pv;
for (Move m : rootMoves[i].pv)
pv += UCIEngine::move(m, pos.is_chess960()) + " ";
// remove last whitespace
if (!pv.empty())
pv.pop_back();
auto wdl = worker.options["UCI_ShowWDL"] ? UCIEngine::wdl(v, pos) : "";
auto bound = rootMoves[i].scoreLowerbound
? "lowerbound"
: (rootMoves[i].scoreUpperbound ? "upperbound" : "");
InfoFull info;
info.depth = d;
info.selDepth = rootMoves[i].selDepth;
info.multiPV = i + 1;
info.score = {v, pos};
info.wdl = wdl;
if (i == pvIdx && !tb && updated) // tablebase- and previous-scores are exact
info.bound = bound;
info.timeMs = time;
info.nodes = nodes;
info.nps = nodes * 1000 / time;
info.tbHits = tbHits;
info.pv = pv;
info.hashfull = tt.hashfull();
updates.onUpdateFull(info);
}
}
// Called in case we have no ponder move before exiting the search,
// for instance, in case we stop the search during a fail high at root.
// We try hard to have a ponder move to return to the GUI,
// otherwise in case of 'ponder on' we have nothing to think about.
bool RootMove::extract_ponder_from_tt(const TranspositionTable& tt, Position& pos) {
StateInfo st;
ASSERT_ALIGNED(&st, Eval::NNUE::CacheLineSize);
assert(pv.size() == 1);
if (pv[0] == Move::none())
return false;
pos.do_move(pv[0], st);
auto [ttHit, ttData, ttWriter] = tt.probe(pos.key());
if (ttHit)
{
if (MoveList<LEGAL>(pos).contains(ttData.move))
pv.push_back(ttData.move);
}
pos.undo_move(pv[0]);
return pv.size() > 1;
}
} // namespace Stockfish
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