along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
+#include <algorithm>
#include <cassert>
#include <cmath>
#include <cstring>
#include <iostream>
#include <sstream>
#include <vector>
-#include <algorithm>
#include "book.h"
#include "evaluate.h"
volatile SignalsType Signals;
LimitsType Limits;
- std::vector<Move> RootMoves;
+ std::vector<Move> SearchMoves;
Position RootPosition;
}
enum NodeType { Root, PV, NonPV, SplitPointRoot, SplitPointPV, SplitPointNonPV };
// RootMove struct is used for moves at the root of the tree. For each root
- // move, we store a score, a node count, and a PV (really a refutation
- // in the case of moves which fail low). Score is normally set at
- // -VALUE_INFINITE for all non-pv moves.
+ // move we store a score, a node count, and a PV (really a refutation in the
+ // case of moves which fail low). Score is normally set at -VALUE_INFINITE for
+ // all non-pv moves.
struct RootMove {
- // RootMove::operator<() is the comparison function used when
- // sorting the moves. A move m1 is considered to be better
- // than a move m2 if it has an higher score
+ RootMove(){}
+ RootMove(Move m) {
+ nodes = 0;
+ score = prevScore = -VALUE_INFINITE;
+ pv.push_back(m);
+ pv.push_back(MOVE_NONE);
+ }
+
bool operator<(const RootMove& m) const { return score < m.score; }
+ bool operator==(const Move& m) const { return pv[0] == m; }
void extract_pv_from_tt(Position& pos);
void insert_pv_in_tt(Position& pos);
std::vector<Move> pv;
};
- // RootMoveList struct is mainly a std::vector of RootMove objects
- struct RootMoveList : public std::vector<RootMove> {
-
- void init(Position& pos, Move rootMoves[]);
- RootMove* find(const Move& m, int startIndex = 0);
-
- int bestMoveChanges;
- };
-
/// Constants
/// Namespace variables
- RootMoveList Rml;
+ std::vector<RootMove> RootMoves;
size_t MultiPV, UCIMultiPV, MultiPVIdx;
TimeManager TimeMgr;
+ int BestMoveChanges;
int SkillLevel;
bool SkillLevelEnabled;
History H;
/// Local functions
- Move id_loop(Position& pos, Move rootMoves[], Move* ponderMove);
+ Move id_loop(Position& pos, Move* ponderMove);
template <NodeType NT>
Value search(Position& pos, Stack* ss, Value alpha, Value beta, Depth depth);
Value refine_eval(const TTEntry* tte, Value defaultEval, int ply);
void update_history(const Position& pos, Move move, Depth depth, Move movesSearched[], int moveCount);
void do_skill_level(Move* best, Move* ponder);
-
int elapsed_time(bool reset = false);
string score_to_uci(Value v, Value alpha = -VALUE_INFINITE, Value beta = VALUE_INFINITE);
string speed_to_uci(int64_t nodes);
string pretty_pv(Position& pos, int depth, Value score, int time, Move pv[]);
string depth_to_uci(Depth depth);
- // MovePickerExt template class extends MovePicker and allows to choose at compile
- // time the proper moves source according to the type of node. In the default case
- // we simply create and use a standard MovePicker object.
+ // MovePickerExt class template extends MovePicker and allows to choose at
+ // compile time the proper moves source according to the type of node. In the
+ // default case we simply create and use a standard MovePicker object.
template<bool SpNode> struct MovePickerExt : public MovePicker {
MovePickerExt(const Position& p, Move ttm, Depth d, const History& h, Stack* ss, Value b)
return os << move_to_uci(m, chess960);
}
- // When formatting a move for std::cout we must know if we are in Chess960
- // or not. To keep using the handy operator<<() on the move the trick is to
- // embed this flag in the stream itself. Function-like named enum set960 is
- // used as a custom manipulator and the stream internal general-purpose array,
- // accessed through ios_base::iword(), is used to pass the flag to the move's
- // operator<<() that will read it to properly format castling moves.
+ // When formatting a move for std::cout we must know if we are in Chess960 or
+ // not. To keep using the handy operator<<() on the move the trick is to embed
+ // this flag in the stream itself. Function-like named enum set960 is used as
+ // a custom manipulator and the stream internal general-purpose array, accessed
+ // through ios_base::iword(), is used to pass the flag to the move's operator<<
+ // that will read it to properly format castling moves.
enum set960 {};
- std::ostream& operator<< (std::ostream& os, const set960& f) {
+ std::ostream& operator<<(std::ostream& os, const set960& f) {
- os.iword(0) = int(f);
+ os.iword(0) = f;
return os;
}
}
UCIMultiPV = Options["MultiPV"].value<size_t>();
- SkillLevel = Options["Skill Level"].value<size_t>();
+ SkillLevel = Options["Skill Level"].value<int>();
// Do we have to play with skill handicap? In this case enable MultiPV that
// we will use behind the scenes to retrieve a set of possible moves.
// We're ready to start thinking. Call the iterative deepening loop function
Move ponderMove = MOVE_NONE;
- Move bestMove = id_loop(pos, &RootMoves[0], &ponderMove);
+ Move bestMove = id_loop(pos, &ponderMove);
// Stop timer and send all the slaves to sleep, if not already sleeping
Threads.set_timer(0);
// with increasing depth until the allocated thinking time has been consumed,
// user stops the search, or the maximum search depth is reached.
- Move id_loop(Position& pos, Move rootMoves[], Move* ponderMove) {
+ Move id_loop(Position& pos, Move* ponderMove) {
Stack ss[PLY_MAX_PLUS_2];
Value bestValues[PLY_MAX_PLUS_2];
memset(ss, 0, 4 * sizeof(Stack));
TT.new_search();
H.clear();
+ RootMoves.clear();
*ponderMove = bestMove = skillBest = skillPonder = MOVE_NONE;
depth = aspirationDelta = 0;
bestValue = alpha = -VALUE_INFINITE, beta = VALUE_INFINITE;
ss->currentMove = MOVE_NULL; // Hack to skip update gains
- Rml.init(pos, rootMoves);
+
+ for (MoveList<MV_LEGAL> ml(pos); !ml.end(); ++ml)
+ if ( SearchMoves.empty()
+ || std::count(SearchMoves.begin(), SearchMoves.end(), ml.move()))
+ RootMoves.push_back(RootMove(ml.move()));
// Handle special case of searching on a mate/stalemate position
- if (Rml.empty())
+ if (RootMoves.empty())
{
cout << "info" << depth_to_uci(DEPTH_ZERO)
<< score_to_uci(pos.in_check() ? -VALUE_MATE : VALUE_DRAW, alpha, beta) << endl;
while (!Signals.stop && ++depth <= PLY_MAX && (!Limits.maxDepth || depth <= Limits.maxDepth))
{
// Save now last iteration's scores, before Rml moves are reordered
- for (size_t i = 0; i < Rml.size(); i++)
- Rml[i].prevScore = Rml[i].score;
+ for (size_t i = 0; i < RootMoves.size(); i++)
+ RootMoves[i].prevScore = RootMoves[i].score;
- Rml.bestMoveChanges = 0;
+ BestMoveChanges = 0;
// MultiPV loop. We perform a full root search for each PV line
- for (MultiPVIdx = 0; MultiPVIdx < std::min(MultiPV, Rml.size()); MultiPVIdx++)
+ for (MultiPVIdx = 0; MultiPVIdx < std::min(MultiPV, RootMoves.size()); MultiPVIdx++)
{
// Calculate dynamic aspiration window based on previous iterations
- if (depth >= 5 && abs(Rml[MultiPVIdx].prevScore) < VALUE_KNOWN_WIN)
+ if (depth >= 5 && abs(RootMoves[MultiPVIdx].prevScore) < VALUE_KNOWN_WIN)
{
int prevDelta1 = bestValues[depth - 1] - bestValues[depth - 2];
int prevDelta2 = bestValues[depth - 2] - bestValues[depth - 3];
aspirationDelta = std::min(std::max(abs(prevDelta1) + abs(prevDelta2) / 2, 16), 24);
aspirationDelta = (aspirationDelta + 7) / 8 * 8; // Round to match grainSize
- alpha = std::max(Rml[MultiPVIdx].prevScore - aspirationDelta, -VALUE_INFINITE);
- beta = std::min(Rml[MultiPVIdx].prevScore + aspirationDelta, VALUE_INFINITE);
+ alpha = std::max(RootMoves[MultiPVIdx].prevScore - aspirationDelta, -VALUE_INFINITE);
+ beta = std::min(RootMoves[MultiPVIdx].prevScore + aspirationDelta, VALUE_INFINITE);
}
else
{
// we want to keep the same order for all the moves but the new
// PV that goes to the front. Note that in case of MultiPV search
// the already searched PV lines are preserved.
- sort<RootMove>(Rml.begin() + MultiPVIdx, Rml.end());
+ sort<RootMove>(RootMoves.begin() + MultiPVIdx, RootMoves.end());
// In case we have found an exact score and we are going to leave
// the fail high/low loop then reorder the PV moves, otherwise
// leave the last PV move in its position so to be searched again.
// Of course this is needed only in MultiPV search.
if (MultiPVIdx && bestValue > alpha && bestValue < beta)
- sort<RootMove>(Rml.begin(), Rml.begin() + MultiPVIdx);
+ sort<RootMove>(RootMoves.begin(), RootMoves.begin() + MultiPVIdx);
// Write PV back to transposition table in case the relevant entries
// have been overwritten during the search.
for (size_t i = 0; i <= MultiPVIdx; i++)
- Rml[i].insert_pv_in_tt(pos);
+ RootMoves[i].insert_pv_in_tt(pos);
// If search has been stopped exit the aspiration window loop,
// note that sorting and writing PV back to TT is safe becuase
// protocol requires to send all the PV lines also if are still
// to be searched and so refer to the previous search's score.
if ((bestValue > alpha && bestValue < beta) || elapsed_time() > 2000)
- for (size_t i = 0; i < std::min(UCIMultiPV, Rml.size()); i++)
+ for (size_t i = 0; i < std::min(UCIMultiPV, RootMoves.size()); i++)
{
bool updated = (i <= MultiPVIdx);
continue;
Depth d = (updated ? depth : depth - 1) * ONE_PLY;
- Value s = (updated ? Rml[i].score : Rml[i].prevScore);
+ Value s = (updated ? RootMoves[i].score : RootMoves[i].prevScore);
cout << "info"
<< depth_to_uci(d)
<< (i == MultiPVIdx ? score_to_uci(s, alpha, beta) : score_to_uci(s))
<< speed_to_uci(pos.nodes_searched())
- << pv_to_uci(&Rml[i].pv[0], i + 1, pos.is_chess960())
+ << pv_to_uci(&RootMoves[i].pv[0], i + 1, pos.is_chess960())
<< endl;
}
} while (abs(bestValue) < VALUE_KNOWN_WIN);
}
- bestMove = Rml[0].pv[0];
- *ponderMove = Rml[0].pv[1];
+ bestMove = RootMoves[0].pv[0];
+ *ponderMove = RootMoves[0].pv[1];
bestValues[depth] = bestValue;
- bestMoveChanges[depth] = Rml.bestMoveChanges;
+ bestMoveChanges[depth] = BestMoveChanges;
// Skills: Do we need to pick now the best and the ponder moves ?
if (SkillLevelEnabled && depth == 1 + SkillLevel)
if (Options["Use Search Log"].value<bool>())
{
Log log(Options["Search Log Filename"].value<string>());
- log << pretty_pv(pos, depth, bestValue, elapsed_time(), &Rml[0].pv[0]) << endl;
+ log << pretty_pv(pos, depth, bestValue, elapsed_time(), &RootMoves[0].pv[0]) << endl;
}
// Filter out startup noise when monitoring best move stability
excludedMove = ss->excludedMove;
posKey = excludedMove ? pos.get_exclusion_key() : pos.get_key();
tte = TT.probe(posKey);
- ttMove = RootNode ? Rml[MultiPVIdx].pv[0] : tte ? tte->move() : MOVE_NONE;
+ ttMove = RootNode ? RootMoves[MultiPVIdx].pv[0] : tte ? tte->move() : MOVE_NONE;
// At PV nodes we check for exact scores, while at non-PV nodes we check for
// a fail high/low. Biggest advantage at probing at PV nodes is to have a
// At root obey the "searchmoves" option and skip moves not listed in Root
// Move List, as a consequence any illegal move is also skipped. In MultiPV
// mode we also skip PV moves which have been already searched.
- if (RootNode && !Rml.find(move, MultiPVIdx))
+ if (RootNode && !std::count(RootMoves.begin() + MultiPVIdx, RootMoves.end(), move))
continue;
// At PV and SpNode nodes we want all moves to be legal since the beginning
// be trusted, and we don't update the best move and/or PV.
if (RootNode && !Signals.stop)
{
- RootMove* rm = Rml.find(move);
- rm->nodes += pos.nodes_searched() - nodes;
+ RootMove& rm = *std::find(RootMoves.begin(), RootMoves.end(), move);
+ rm.nodes += pos.nodes_searched() - nodes;
// PV move or new best move ?
if (isPvMove || value > alpha)
{
- rm->score = value;
- rm->extract_pv_from_tt(pos);
+ rm.score = value;
+ rm.extract_pv_from_tt(pos);
// We record how often the best move has been changed in each
// iteration. This information is used for time management: When
// the best move changes frequently, we allocate some more time.
if (!isPvMove && MultiPV == 1)
- Rml.bestMoveChanges++;
+ BestMoveChanges++;
}
else
// All other moves but the PV are set to the lowest value, this
// is not a problem when sorting becuase sort is stable and move
// position in the list is preserved, just the PV is pushed up.
- rm->score = -VALUE_INFINITE;
+ rm.score = -VALUE_INFINITE;
}
string depth_to_uci(Depth depth) {
std::stringstream s;
+ int selDepth = 0;
// Retrieve max searched depth among threads
- int selDepth = 0;
for (int i = 0; i < Threads.size(); i++)
if (Threads[i].maxPly > selDepth)
selDepth = Threads[i].maxPly;
- s << " depth " << depth / ONE_PLY << " seldepth " << selDepth;
+ s << " depth " << depth / ONE_PLY << " seldepth " << selDepth;
return s.str();
}
- // pretty_pv() creates a human-readable string from a position and a PV.
- // It is used to write search information to the log file (which is created
- // when the UCI parameter "Use Search Log" is "true"). It uses the two helpers
- // time_to_string() and score_to_string() to format time and score respectively.
+ // pretty_pv() creates a human-readable string from a position and a PV. It is
+ // used to write search information to the log file (which is created when the
+ // UCI parameter "Use Search Log" is "true"). It uses the two below helper to
+ // pretty format time and score respectively.
string time_to_string(int millisecs) {
if (hours)
s << hours << ':';
- s << std::setfill('0') << std::setw(2) << minutes << ':' << std::setw(2) << seconds;
+ s << std::setfill('0') << std::setw(2) << minutes << ':'
+ << std::setw(2) << seconds;
return s.str();
}
else if (v <= VALUE_MATED_IN_PLY_MAX)
s << "-#" << (VALUE_MATE + v) / 2;
else
- s << std::setprecision(2) << std::fixed << std::showpos << float(v) / PawnValueMidgame;
+ s << std::setprecision(2) << std::fixed << std::showpos
+ << float(v) / PawnValueMidgame;
return s.str();
}
const int64_t K = 1000;
const int64_t M = 1000000;
- const int startColumn = 28;
- const size_t maxLength = 80 - startColumn;
StateInfo state[PLY_MAX_PLUS_2], *st = state;
Move* m = pv;
- string san;
+ string san, padding;
+ size_t length;
std::stringstream s;
- size_t length = 0;
- // First print depth, score, time and searched nodes...
s << set960(pos.is_chess960())
<< std::setw(2) << depth
<< std::setw(8) << score_to_string(value)
else
s << std::setw(7) << pos.nodes_searched() / M << "M ";
- // ...then print the full PV line in short algebraic notation
+ padding = string(s.str().length(), ' ');
+ length = padding.length();
+
while (*m != MOVE_NONE)
{
san = move_to_san(pos, *m);
- length += san.length() + 1;
- if (length > maxLength)
+ if (length + san.length() > 80)
{
- length = san.length() + 1;
- s << "\n" + string(startColumn, ' ');
+ s << "\n" + padding;
+ length = padding.length();
}
+
s << san << ' ';
+ length += san.length() + 1;
pos.do_move(*m++, *st++);
}
// Restore original position before to leave
- while (m != pv) pos.undo_move(*--m);
+ while (m != pv)
+ pos.undo_move(*--m);
return s.str();
}
static RKISS rk;
- // Rml list is already sorted by score in descending order
- int s;
- size_t size = std::min(MultiPV, Rml.size());
- int max_s = -VALUE_INFINITE;
- int max = Rml[0].score;
- int var = std::min(max - Rml[size - 1].score, int(PawnValueMidgame));
- int wk = 120 - 2 * SkillLevel;
-
- // PRNG sequence should be non deterministic
+ // PRNG sequence should be not deterministic
for (int i = abs(get_system_time() % 50); i > 0; i--)
rk.rand<unsigned>();
- // Choose best move. For each move's score we add two terms both dependent
- // on wk, one deterministic and bigger for weaker moves, and one random,
+ // Rml list is already sorted by score in descending order
+ size_t size = std::min(MultiPV, RootMoves.size());
+ int variance = std::min(RootMoves[0].score - RootMoves[size - 1].score, PawnValueMidgame);
+ int weakness = 120 - 2 * SkillLevel;
+ int max_s = -VALUE_INFINITE;
+
+ // Choose best move. For each move score we add two terms both dependent on
+ // weakness, one deterministic and bigger for weaker moves, and one random,
// then we choose the move with the resulting highest score.
for (size_t i = 0; i < size; i++)
{
- s = Rml[i].score;
+ int s = RootMoves[i].score;
// Don't allow crazy blunders even at very low skills
- if (i > 0 && Rml[i-1].score > s + EasyMoveMargin)
+ if (i > 0 && RootMoves[i-1].score > s + EasyMoveMargin)
break;
- // This is our magical formula
- s += ((max - s) * wk + var * (rk.rand<unsigned>() % wk)) / 128;
+ // This is our magic formula
+ s += ( weakness * int(RootMoves[0].score - s)
+ + variance * (rk.rand<unsigned>() % weakness)) / 128;
if (s > max_s)
{
max_s = s;
- *best = Rml[i].pv[0];
- *ponder = Rml[i].pv[1];
+ *best = RootMoves[i].pv[0];
+ *ponder = RootMoves[i].pv[1];
}
}
}
- // RootMove and RootMoveList method's definitions
-
- void RootMoveList::init(Position& pos, Move rootMoves[]) {
-
- Move* sm;
- bestMoveChanges = 0;
- clear();
-
- // Generate all legal moves and add them to RootMoveList
- for (MoveList<MV_LEGAL> ml(pos); !ml.end(); ++ml)
- {
- // If we have a rootMoves[] list then verify the move
- // is in the list before to add it.
- for (sm = rootMoves; *sm && *sm != ml.move(); sm++) {}
-
- if (sm != rootMoves && *sm != ml.move())
- continue;
-
- RootMove rm;
- rm.pv.push_back(ml.move());
- rm.pv.push_back(MOVE_NONE);
- rm.score = rm.prevScore = -VALUE_INFINITE;
- rm.nodes = 0;
- push_back(rm);
- }
- }
-
- RootMove* RootMoveList::find(const Move& m, int startIndex) {
-
- for (size_t i = startIndex; i < size(); i++)
- if ((*this)[i].pv[0] == m)
- return &(*this)[i];
-
- return NULL;
- }
-
-
// extract_pv_from_tt() builds a PV by adding moves from the transposition table.
// We consider also failing high nodes and not only VALUE_TYPE_EXACT nodes. This
// allow to always have a ponder move even when we fail high at root and also a
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