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BadFish/src/search.cpp
FauziAkram 0282edc0b0 Simplify bonus formula 
Give full bonus instead of half.

Passed STC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 23872 W: 6254 L: 6018 D: 11600
Ptnml(0-2): 80, 2691, 6152, 2939, 74
https://tests.stockfishchess.org/tests/view/673b709686d5ee47d953f19d

Passed LTC:
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 42894 W: 10924 L: 10725 D: 21245
Ptnml(0-2): 30, 4592, 12011, 4777, 37
https://tests.stockfishchess.org/tests/view/673bb50386d5ee47d953f1eb

closes https://github.com/official-stockfish/Stockfish/pull/5683

Bench: 836558
2024-11-22 23:23:42 +01:00

2170 lines
86 KiB
C++
Raw Blame History

/*
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 <chrono>
#include <cmath>
#include <cstdint>
#include <cstdlib>
#include <initializer_list>
#include <iostream>
#include <list>
#include <ratio>
#include <string>
#include <utility>
#include "evaluate.h"
#include "history.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 "uci.h"
#include "ucioption.h"
namespace Stockfish {
namespace TB = Tablebases;
void syzygy_extend_pv(const OptionsMap& options,
const Search::LimitsType& limits,
Stockfish::Position& pos,
Stockfish::Search::RootMove& rootMove,
Value& v);
using Eval::evaluate;
using namespace Search;
namespace {
// Futility margin
Value futility_margin(Depth d, bool noTtCutNode, bool improving, bool oppWorsening) {
Value futilityMult = 109 - 27 * noTtCutNode;
Value improvingDeduction = improving * futilityMult * 2;
Value worseningDeduction = oppWorsening * futilityMult / 3;
return futilityMult * d - improvingDeduction - worseningDeduction;
}
constexpr int futility_move_count(bool improving, Depth depth) {
return (3 + depth * depth) / (2 - improving);
}
// 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, Stack* ss) {
const Color us = pos.side_to_move();
const auto m = (ss - 1)->currentMove;
const auto pcv = w.pawnCorrectionHistory[us][pawn_structure_index<Correction>(pos)];
const auto macv = w.majorPieceCorrectionHistory[us][major_piece_index(pos)];
const auto micv = w.minorPieceCorrectionHistory[us][minor_piece_index(pos)];
const auto wnpcv = w.nonPawnCorrectionHistory[WHITE][us][non_pawn_index<WHITE>(pos)];
const auto bnpcv = w.nonPawnCorrectionHistory[BLACK][us][non_pawn_index<BLACK>(pos)];
int cntcv = 1;
if (m.is_ok())
cntcv = int((*(ss - 2)->continuationCorrectionHistory)[pos.piece_on(m.to_sq())][m.to_sq()]);
const auto cv =
(6384 * pcv + 3583 * macv + 6492 * micv + 6725 * (wnpcv + bnpcv) + cntcv * 5880) / 131072;
v += cv;
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::min(168 * d - 100, 1718); }
// History and stats update malus, based on depth
int stat_malus(Depth d) { return std::min(768 * d - 257, 2351); }
// 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); }
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_quiet_histories(
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,
Square prevSq,
ValueList<Move, 32>& quietsSearched,
ValueList<Move, 32>& capturesSearched,
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::ensure_network_replicated() {
// Access once to force lazy initialization.
// We do this because we want to avoid initialization during search.
(void) (networks[numaAccessToken]);
}
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.
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)->continuationCorrectionHistory = &this->continuationCorrectionHistory[NO_PIECE][0];
(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;
lowPlyHistory.fill(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
delta = 5 + std::abs(rootMoves[pvIdx].meanSquaredScore) / 13461;
Value avg = rootMoves[pvIdx].averageScore;
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] = 150 * avg / (std::abs(avg) + 85);
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 before a re-search. To avoid
// excessive output that could hang GUIs like Fritz 19, only start
// at nodes > 10M (rather than depth N, which can be reached quickly)
if (mainThread && multiPV == 1 && (bestValue <= alpha || bestValue >= beta)
&& nodes > 10000000)
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 || nodes > 10000000)
// 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 = (11 + 2 * (mainThread->bestPreviousAverageScore - bestValue)
+ (mainThread->iterValue[iterIdx] - bestValue))
/ 100.0;
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();
double recapture = limits.capSq == rootMoves[0].pv[0].to_sq() ? 0.955 : 1.005;
double totalTime =
mainThread->tm.optimum() * fallingEval * reduction * bestMoveInstability * 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)));
}
// Reset histories, usually before a new game
void Search::Worker::clear() {
mainHistory.fill(0);
lowPlyHistory.fill(0);
captureHistory.fill(-758);
pawnHistory.fill(-1158);
pawnCorrectionHistory.fill(0);
majorPieceCorrectionHistory.fill(0);
minorPieceCorrectionHistory.fill(0);
nonPawnCorrectionHistory[WHITE].fill(0);
nonPawnCorrectionHistory[BLACK].fill(0);
for (auto& to : continuationCorrectionHistory)
for (auto& h : to)
h->fill(0);
for (bool inCheck : {false, true})
for (StatsType c : {NoCaptures, Captures})
for (auto& to : continuationHistory[inCheck][c])
for (auto& h : to)
h->fill(-645);
for (size_t i = 1; i < reductions.size(); ++i)
reductions[i] = int((19.43 + 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;
const bool allNode = !(PvNode || cutNode);
// 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
if (!rootNode && alpha < VALUE_DRAW && pos.upcoming_repetition(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];
StateInfo st;
ASSERT_ALIGNED(&st, Eval::NNUE::CacheLineSize);
Key posKey;
Move move, excludedMove, bestMove;
Depth extension, newDepth;
Value bestValue, value, eval, maxValue, probCutBeta;
bool givesCheck, improving, priorCapture, opponentWorsening;
bool capture, ttCapture;
Piece movedPiece;
ValueList<Move, 32> capturesSearched;
ValueList<Move, 32> quietsSearched;
// Step 1. Initialize node
Worker* thisThread = this;
ss->inCheck = pos.checkers();
priorCapture = pos.captured_piece();
Color us = pos.side_to_move();
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)->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))
&& (cutNode == (ttData.value >= beta) || depth > 8))
{
// 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_histories(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 = (ss - 2)->staticEval;
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, ss);
// 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, ss);
// 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), -1831, 1428) + 623;
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;
}
// 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 go back until we weren't in check) and is
// false otherwise. The improving flag is used in various pruning heuristics.
improving = ss->staticEval > (ss - 2)->staticEval;
opponentWorsening = ss->staticEval + (ss - 1)->staticEval > 2;
// Step 7. Razoring (~1 Elo)
// If eval is really low, check with qsearch if we can exceed alpha. If the
// search suggests we cannot exceed alpha, return a speculative fail low.
if (eval < alpha - 469 - 307 * 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 < 14
&& eval - futility_margin(depth, cutNode && !ss->ttHit, improving, opponentWorsening)
- (ss - 1)->statScore / 290
>= 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;
improving |= ss->staticEval >= beta + 100;
// Step 9. Null move search with verification search (~35 Elo)
if (cutNode && (ss - 1)->currentMove != Move::null() && eval >= beta
&& ss->staticEval >= beta - 21 * depth + 421 && !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) / 235, 7) + depth / 3 + 5;
ss->currentMove = Move::null();
ss->continuationHistory = &thisThread->continuationHistory[0][0][NO_PIECE][0];
ss->continuationCorrectionHistory = &thisThread->continuationCorrectionHistory[NO_PIECE][0];
pos.do_null_move(st, tt);
Value nullValue = -search<NonPV>(pos, ss + 1, -beta, -beta + 1, depth - R, false);
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.
if (PvNode && !ttData.move)
depth -= 3;
// 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 >= 7 && (!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 + 187 - 53 * improving - 27 * opponentWorsening;
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);
Piece captured;
while ((move = mp.next_move()) != Move::none())
{
assert(move.is_ok());
if (move == excludedMove)
continue;
if (!pos.legal(move))
continue;
assert(pos.capture_stage(move));
movedPiece = pos.moved_piece(move);
captured = pos.piece_on(move.to_sq());
// 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()];
ss->continuationCorrectionHistory =
&this->continuationCorrectionHistory[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)
{
thisThread->captureHistory[movedPiece][move.to_sq()][type_of(captured)]
<< stat_bonus(depth - 2);
// 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 (~4 Elo)
probCutBeta = beta + 417;
if ((ttData.bound & BOUND_LOWER) && ttData.depth >= depth - 4 && ttData.value >= probCutBeta
&& std::abs(beta) < VALUE_TB_WIN_IN_MAX_PLY
&& std::abs(ttData.value) < 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};
MovePicker mp(pos, ttData.move, depth, &thisThread->mainHistory, &thisThread->lowPlyHistory,
&thisThread->captureHistory, contHist, &thisThread->pawnHistory, ss->ply);
value = bestValue;
int moveCount = 0;
// Step 13. 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());
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() && nodes > 10000000)
{
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)
if (moveCount >= futility_move_count(improving, depth))
mp.skip_quiet_moves();
// Reduced depth of the next LMR search
int lmrDepth = newDepth - r / 1024;
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 + 253 * lmrDepth
+ PieceValue[capturedPiece] + captHist / 7;
if (futilityValue <= alpha)
continue;
}
// SEE based pruning for captures and checks (~11 Elo)
int seeHist = std::clamp(captHist / 33, -161 * depth, 156 * depth);
if (!pos.see_ge(move, -162 * 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 (history < -3884 * depth)
continue;
history += 2 * thisThread->mainHistory[us][move.from_to()];
lmrDepth += history / 3609;
Value futilityValue =
ss->staticEval + (bestValue < ss->staticEval - 45 ? 140 : 43) + 141 * 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 = futilityValue;
continue;
}
lmrDepth = std::max(lmrDepth, 0);
// Prune moves with negative SEE (~4 Elo)
if (!pos.see_ge(move, -25 * 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 (~76 Elo, ~170 nElo). 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 > 33) + ss->ttPv
&& std::abs(ttData.value) < VALUE_TB_WIN_IN_MAX_PLY && (ttData.bound & BOUND_LOWER)
&& ttData.depth >= depth - 3)
{
Value singularBeta = ttData.value - (56 + 79 * (ss->ttPv && !PvNode)) * depth / 64;
Depth singularDepth = newDepth / 2;
ss->excludedMove = move;
value =
search<NonPV>(pos, ss, singularBeta - 1, singularBeta, singularDepth, cutNode);
ss->excludedMove = Move::none();
if (value < singularBeta)
{
int doubleMargin = 249 * PvNode - 194 * !ttCapture;
int tripleMargin = 94 + 287 * PvNode - 249 * !ttCapture + 99 * ss->ttPv;
extension = 1 + (value < singularBeta - doubleMargin)
+ (value < singularBeta - tripleMargin);
depth += ((!PvNode) && (depth < 14));
}
// 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 (~1 Elo at LTC)
else if (PvNode && move.to_sq() == prevSq
&& thisThread->captureHistory[movedPiece][move.to_sq()]
[type_of(pos.piece_on(move.to_sq()))]
> 4321)
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()];
ss->continuationCorrectionHistory =
&thisThread->continuationCorrectionHistory[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 -= 1024 + (ttData.value > alpha) * 1024 + (ttData.depth >= depth) * 1024;
// Decrease reduction for PvNodes (~0 Elo on STC, ~2 Elo on LTC)
if (PvNode)
r -= 1024;
// These reduction adjustments have no proven non-linear scaling
// Increase reduction for cut nodes (~4 Elo)
if (cutNode)
r += 2518 - (ttData.depth >= depth && ss->ttPv) * 991;
// Increase reduction if ttMove is a capture but the current move is not a capture (~3 Elo)
if (ttCapture && !capture)
r += 1043 + (depth < 8) * 999;
// Increase reduction if next ply has a lot of fail high (~5 Elo)
if ((ss + 1)->cutoffCnt > 3)
r += 938 + allNode * 960;
// For first picked move (ttMove) reduce reduction (~3 Elo)
else if (move == ttData.move)
r -= 1879;
if (capture)
ss->statScore =
thisThread->captureHistory[movedPiece][move.to_sq()][type_of(pos.captured_piece())]
- 11000;
else
ss->statScore = 2 * thisThread->mainHistory[us][move.from_to()]
+ (*contHist[0])[movedPiece][move.to_sq()]
+ (*contHist[1])[movedPiece][move.to_sq()] - 3996;
// Decrease/increase reduction for moves with a good/bad history (~8 Elo)
r -= ss->statScore * 1287 / 16384;
// Step 17. Late moves reduction / extension (LMR, ~117 Elo)
if (depth >= 2 && moveCount > 1)
{
// 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 / 1024, newDepth + !allNode));
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 + 42 + 2 * newDepth); // (~1 Elo)
const bool doShallowerSearch = value < bestValue + 10; // (~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 = 2 * (value >= beta) * stat_bonus(newDepth);
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 += 2037;
// 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 > 2983), !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();
// Extend move from transposition table if we are about to dive into qsearch.
if (move == ttData.move && ss->ply <= thisThread->rootDepth * 2)
newDepth = std::max(newDepth, 1);
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, principal variation nor transposition table.
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 ? (value + rm.averageScore) / 2 : value;
rm.meanSquaredScore = rm.meanSquaredScore != -VALUE_INFINITE * VALUE_INFINITE
? (value * std::abs(value) + rm.meanSquaredScore) / 2
: value * std::abs(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 >= 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 += !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 < 14 && 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.push_back(move);
else
quietsSearched.push_back(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, prevSq, quietsSearched, capturesSearched, depth);
// Bonus for prior countermove that caused the fail low
else if (!priorCapture && prevSq != SQ_NONE)
{
int bonus = (117 * (depth > 5) + 39 * !allNode + 168 * ((ss - 1)->moveCount > 8)
+ 115 * (!ss->inCheck && bestValue <= ss->staticEval - 108)
+ 119 * (!(ss - 1)->inCheck && bestValue <= -(ss - 1)->staticEval - 83));
// Proportional to "how much damage we have to undo"
bonus += std::min(-(ss - 1)->statScore / 113, 300);
bonus = std::max(bonus, 0);
update_continuation_histories(ss - 1, pos.piece_on(prevSq), prevSq,
stat_bonus(depth) * bonus / 93);
thisThread->mainHistory[~us][((ss - 1)->currentMove).from_to()]
<< stat_bonus(depth) * bonus / 179;
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 / 24;
}
// Bonus when search fails low and there is a TT move
else if (ttData.move && !allNode)
thisThread->mainHistory[us][ttData.move.from_to()] << stat_bonus(depth) * 23 / 100;
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. Note that the
// 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))
{
const auto m = (ss - 1)->currentMove;
auto bonus = std::clamp(int(bestValue - ss->staticEval) * depth / 8,
-CORRECTION_HISTORY_LIMIT / 4, CORRECTION_HISTORY_LIMIT / 4);
thisThread->pawnCorrectionHistory[us][pawn_structure_index<Correction>(pos)]
<< bonus * 107 / 128;
thisThread->majorPieceCorrectionHistory[us][major_piece_index(pos)] << bonus * 162 / 128;
thisThread->minorPieceCorrectionHistory[us][minor_piece_index(pos)] << bonus * 148 / 128;
thisThread->nonPawnCorrectionHistory[WHITE][us][non_pawn_index<WHITE>(pos)]
<< bonus * 122 / 128;
thisThread->nonPawnCorrectionHistory[BLACK][us][non_pawn_index<BLACK>(pos)]
<< bonus * 185 / 128;
if (m.is_ok())
(*(ss - 2)->continuationCorrectionHistory)[pos.piece_on(m.to_sq())][m.to_sq()] << bonus;
}
assert(bestValue > -VALUE_INFINITE && bestValue < VALUE_INFINITE);
return bestValue;
}
// Quiescence search function, which is called by the main search function with
// depth zero, or recursively with further decreasing depth. 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 (~155 Elo).
// See https://www.chessprogramming.org/Horizon_Effect
// and https://www.chessprogramming.org/Quiescence_Search
template<NodeType nodeType>
Value Search::Worker::qsearch(Position& pos, Stack* ss, Value alpha, Value beta) {
static_assert(nodeType != Root);
constexpr bool PvNode = nodeType == PV;
assert(alpha >= -VALUE_INFINITE && alpha < beta && beta <= VALUE_INFINITE);
assert(PvNode || (alpha == beta - 1));
// Check if we have an upcoming move that draws by repetition (~1 Elo)
if (alpha < VALUE_DRAW && pos.upcoming_repetition(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);
// 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 >= DEPTH_QS
&& 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, ss);
// 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 opposite 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, ss);
}
// Stand pat. Return immediately if static value is at least beta
if (bestValue >= beta)
{
if (std::abs(bestValue) < VALUE_TB_WIN_IN_MAX_PLY)
bestValue = (bestValue + beta) / 2;
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 + 306;
}
const PieceToHistory* contHist[] = {(ss - 1)->continuationHistory,
(ss - 2)->continuationHistory};
Square prevSq = ((ss - 1)->currentMove).is_ok() ? ((ss - 1)->currentMove).to_sq() : SQ_NONE;
// Initialize a MovePicker object for the current position, and prepare to search
// the moves. We presently use two stages of move generator in quiescence search:
// captures, or evasions only when in check.
MovePicker mp(pos, ttData.move, DEPTH_QS, &thisThread->mainHistory, &thisThread->lowPlyHistory,
&thisThread->captureHistory, contHist, &thisThread->pawnHistory, ss->ply);
// 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());
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 exchange evaluation is low enough
// we can prune this move. (~2 Elo)
if (!pos.see_ge(move, alpha - futilityBase))
{
bestValue = std::min(alpha, futilityBase);
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()]
<= 5095)
continue;
// Do not search moves with bad enough SEE values (~5 Elo)
if (!pos.see_ge(move, -83))
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()];
ss->continuationCorrectionHistory =
&thisThread->continuationCorrectionHistory[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);
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 are
// 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. The 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, DEPTH_QS, 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 + 1304 - delta * 814 / rootDelta) + (!i && reductionScale > 1423) * 1135;
}
// 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,
Square prevSq,
ValueList<Move, 32>& quietsSearched,
ValueList<Move, 32>& capturesSearched,
Depth depth) {
CapturePieceToHistory& captureHistory = workerThread.captureHistory;
Piece moved_piece = pos.moved_piece(bestMove);
PieceType captured;
int bonus = stat_bonus(depth);
int malus = stat_malus(depth);
if (!pos.capture_stage(bestMove))
{
update_quiet_histories(pos, ss, workerThread, bestMove, bonus);
// Decrease stats for all non-best quiet moves
for (Move move : quietsSearched)
update_quiet_histories(pos, ss, workerThread, move, -malus);
}
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] << bonus;
}
// Extra penalty for a quiet early move that was not a TT move in
// previous ply when it gets refuted.
if (prevSq != SQ_NONE && ((ss - 1)->moveCount == 1 + (ss - 1)->ttHit) && !pos.captured_piece())
update_continuation_histories(ss - 1, pos.piece_on(prevSq), prevSq, -malus);
// Decrease stats for all non-best capture moves
for (Move move : capturesSearched)
{
moved_piece = pos.moved_piece(move);
captured = type_of(pos.piece_on(move.to_sq()));
captureHistory[moved_piece][move.to_sq()][captured] << -malus;
}
}
// 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 * 50 / 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_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;
if (ss->ply < LOW_PLY_HISTORY_SIZE)
workerThread.lowPlyHistory[ss->ply][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;
}
}
// 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;
}
// Used to correct and extend PVs for moves that have a TB (but not a mate) score.
// Keeps the search based PV for as long as it is verified to maintain the game
// outcome, truncates afterwards. Finally, extends to mate the PV, providing a
// possible continuation (but not a proven mating line).
void syzygy_extend_pv(const OptionsMap& options,
const Search::LimitsType& limits,
Position& pos,
RootMove& rootMove,
Value& v) {
auto t_start = std::chrono::steady_clock::now();
int moveOverhead = int(options["Move Overhead"]);
// Do not use more than moveOverhead / 2 time, if time management is active
auto time_abort = [&t_start, &moveOverhead, &limits]() -> bool {
auto t_end = std::chrono::steady_clock::now();
return limits.use_time_management()
&& 2 * std::chrono::duration<double, std::milli>(t_end - t_start).count()
> moveOverhead;
};
std::list<StateInfo> sts;
// Step 0, do the rootMove, no correction allowed, as needed for MultiPV in TB.
auto& stRoot = sts.emplace_back();
pos.do_move(rootMove.pv[0], stRoot);
int ply = 1;
// Step 1, walk the PV to the last position in TB with correct decisive score
while (size_t(ply) < rootMove.pv.size())
{
Move& pvMove = rootMove.pv[ply];
RootMoves legalMoves;
for (const auto& m : MoveList<LEGAL>(pos))
legalMoves.emplace_back(m);
Tablebases::Config config = Tablebases::rank_root_moves(options, pos, legalMoves);
RootMove& rm = *std::find(legalMoves.begin(), legalMoves.end(), pvMove);
if (legalMoves[0].tbRank != rm.tbRank)
break;
ply++;
auto& st = sts.emplace_back();
pos.do_move(pvMove, st);
// Do not allow for repetitions or drawing moves along the PV in TB regime
if (config.rootInTB && pos.is_draw(ply))
{
pos.undo_move(pvMove);
ply--;
break;
}
// Full PV shown will thus be validated and end in TB.
// If we cannot validate the full PV in time, we do not show it.
if (config.rootInTB && time_abort())
break;
}
// Resize the PV to the correct part
rootMove.pv.resize(ply);
// Step 2, now extend the PV to mate, as if the user explored syzygy-tables.info
// using top ranked moves (minimal DTZ), which gives optimal mates only for simple
// endgames e.g. KRvK.
while (!pos.is_draw(0))
{
if (time_abort())
break;
RootMoves legalMoves;
for (const auto& m : MoveList<LEGAL>(pos))
{
auto& rm = legalMoves.emplace_back(m);
StateInfo tmpSI;
pos.do_move(m, tmpSI);
// Give a score of each move to break DTZ ties restricting opponent mobility,
// but not giving the opponent a capture.
for (const auto& mOpp : MoveList<LEGAL>(pos))
rm.tbRank -= pos.capture(mOpp) ? 100 : 1;
pos.undo_move(m);
}
// Mate found
if (legalMoves.size() == 0)
break;
// Sort moves according to their above assigned rank.
// This will break ties for moves with equal DTZ in rank_root_moves.
std::stable_sort(
legalMoves.begin(), legalMoves.end(),
[](const Search::RootMove& a, const Search::RootMove& b) { return a.tbRank > b.tbRank; });
// The winning side tries to minimize DTZ, the losing side maximizes it
Tablebases::Config config = Tablebases::rank_root_moves(options, pos, legalMoves, true);
// If DTZ is not available we might not find a mate, so we bail out
if (!config.rootInTB || config.cardinality > 0)
break;
ply++;
Move& pvMove = legalMoves[0].pv[0];
rootMove.pv.push_back(pvMove);
auto& st = sts.emplace_back();
pos.do_move(pvMove, st);
}
// Finding a draw in this function is an exceptional case, that cannot happen
// during engine game play, since we have a winning score, and play correctly
// with TB support. However, it can be that a position is draw due to the 50 move
// rule if it has been been reached on the board with a non-optimal 50 move counter
// (e.g. 8/8/6k1/3B4/3K4/4N3/8/8 w - - 54 106 ) which TB with dtz counter rounding
// cannot always correctly rank. See also
// https://github.com/official-stockfish/Stockfish/issues/5175#issuecomment-2058893495
// We adjust the score to match the found PV. Note that a TB loss score can be
// displayed if the engine did not find a drawing move yet, but eventually search
// will figure it out (e.g. 1kq5/q2r4/5K2/8/8/8/8/7Q w - - 96 1 )
if (pos.is_draw(0))
v = VALUE_DRAW;
// Undo the PV moves
for (auto it = rootMove.pv.rbegin(); it != rootMove.pv.rend(); ++it)
pos.undo_move(*it);
// Inform if we couldn't get a full extension in time
if (time_abort())
sync_cout
<< "info string Syzygy based PV extension requires more time, increase Move Overhead as needed."
<< sync_endl;
}
void SearchManager::pv(Search::Worker& worker,
const ThreadPool& threads,
const TranspositionTable& tt,
Depth depth) {
const auto nodes = threads.nodes_searched();
auto& rootMoves = worker.rootMoves;
auto& pos = worker.rootPos;
size_t pvIdx = worker.pvIdx;
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;
bool isExact = i != pvIdx || tb || !updated; // tablebase- and previous-scores are exact
// Potentially correct and extend the PV, and in exceptional cases v
if (std::abs(v) >= VALUE_TB_WIN_IN_MAX_PLY && std::abs(v) < VALUE_MATE_IN_MAX_PLY
&& ((!rootMoves[i].scoreLowerbound && !rootMoves[i].scoreUpperbound) || isExact))
syzygy_extend_pv(worker.options, worker.limits, pos, rootMoves[i], 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 (!isExact)
info.bound = bound;
TimePoint time = tm.elapsed_time() + 1;
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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