RootMoveList Rml;
// MultiPV mode
- int MultiPV;
+ int MultiPV, UCIMultiPV;
// Time management variables
int SearchStartTime, MaxNodes, MaxDepth, ExactMaxTime;
bool UseLogFile;
std::ofstream LogFile;
+ // Skill level adjustment
+ int SkillLevel;
+ RKISS RK;
+
// Multi-threads manager object
ThreadsManager ThreadsMgr;
PawnEndgameExtension[0] = Options["Pawn Endgame Extension (non-PV nodes)"].value<Depth>();
MateThreatExtension[1] = Options["Mate Threat Extension (PV nodes)"].value<Depth>();
MateThreatExtension[0] = Options["Mate Threat Extension (non-PV nodes)"].value<Depth>();
- MultiPV = Options["MultiPV"].value<int>();
+ UCIMultiPV = Options["MultiPV"].value<int>();
+ SkillLevel = Options["Skill level"].value<int>();
UseLogFile = Options["Use Search Log"].value<bool>();
read_evaluation_uci_options(pos.side_to_move());
+ // 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.
+ MultiPV = (SkillLevel < 20 ? Max(UCIMultiPV, 4) : UCIMultiPV);
+
// Set the number of active threads
ThreadsMgr.read_uci_options();
init_eval(ThreadsMgr.active_threads());
if (!StopRequest && (Pondering || InfiniteSearch))
wait_for_stop_or_ponderhit();
- // Could be both MOVE_NONE when searching on a stalemate position
- cout << "bestmove " << bestMove << " ponder " << ponderMove << endl;
+ // Could be MOVE_NONE when searching on a stalemate position
+ cout << "bestmove " << bestMove;
+
+ // UCI protol is not clear on allowing sending an empty ponder move, instead
+ // it is clear that ponder move is optional. So skip it if empty.
+ if (ponderMove != MOVE_NONE)
+ cout << " ponder " << ponderMove;
+
+ cout << endl;
return !QuitRequest;
}
SearchStack ss[PLY_MAX_PLUS_2];
Value bestValues[PLY_MAX_PLUS_2];
int bestMoveChanges[PLY_MAX_PLUS_2];
- int depth, researchCountFL, researchCountFH, aspirationDelta;
+ int depth, aspirationDelta;
Value value, alpha, beta;
Move bestMove, easyMove;
- // Moves to search are verified and copied
- Rml.init(pos, searchMoves);
-
- // Initialize FIXME move before Rml.init()
+ // Initialize stuff before a new search
+ memset(ss, 0, 4 * sizeof(SearchStack));
TT.new_search();
H.clear();
- memset(ss, 0, 4 * sizeof(SearchStack));
*ponderMove = bestMove = easyMove = MOVE_NONE;
depth = aspirationDelta = 0;
- ss->currentMove = MOVE_NULL; // Hack to skip update_gains()
alpha = -VALUE_INFINITE, beta = VALUE_INFINITE;
+ ss->currentMove = MOVE_NULL; // Hack to skip update_gains()
+
+ // Moves to search are verified and copied
+ Rml.init(pos, searchMoves);
// Handle special case of searching on a mate/stalemate position
if (Rml.size() == 0)
// Iterative deepening loop
while (++depth <= PLY_MAX && (!MaxDepth || depth <= MaxDepth) && !StopRequest)
{
- Rml.bestMoveChanges = researchCountFL = researchCountFH = 0;
- cout << "info depth " << depth << endl;
+ Rml.bestMoveChanges = 0;
+ cout << set960(pos.is_chess960()) << "info depth " << depth << endl;
// Calculate dynamic aspiration window based on previous iterations
if (MultiPV == 1 && depth >= 5 && abs(bestValues[depth - 1]) < VALUE_KNOWN_WIN)
// Start with a small aspiration window and, in case of fail high/low,
// research with bigger window until not failing high/low anymore.
- while (true)
- {
+ do {
// Search starting from ss+1 to allow calling update_gains()
value = search<PV, false, true>(pos, ss+1, alpha, beta, depth * ONE_PLY, 0);
- // Send PV line to GUI and write to transposition table in case the
- // relevant entries have been overwritten during the search.
+ // Write PV back to transposition table in case the relevant entries
+ // have been overwritten during the search.
for (int i = 0; i < Min(MultiPV, (int)Rml.size()); i++)
- {
Rml[i].insert_pv_in_tt(pos);
- cout << set960(pos.is_chess960())
- << Rml[i].pv_info_to_uci(pos, depth, alpha, beta, i) << endl;
- }
// Value cannot be trusted. Break out immediately!
if (StopRequest)
// otherwise exit the fail high/low loop.
if (value >= beta)
{
- beta = Min(beta + aspirationDelta * (1 << researchCountFH), VALUE_INFINITE);
- researchCountFH++;
+ beta = Min(beta + aspirationDelta, VALUE_INFINITE);
+ aspirationDelta += aspirationDelta / 2;
}
else if (value <= alpha)
{
AspirationFailLow = true;
StopOnPonderhit = false;
- alpha = Max(alpha - aspirationDelta * (1 << researchCountFL), -VALUE_INFINITE);
- researchCountFL++;
+ alpha = Max(alpha - aspirationDelta, -VALUE_INFINITE);
+ aspirationDelta += aspirationDelta / 2;
}
else
break;
- }
+
+ } while (abs(value) < VALUE_KNOWN_WIN);
// Collect info about search result
bestMove = Rml[0].pv[0];
+ *ponderMove = Rml[0].pv[1];
bestValues[depth] = value;
bestMoveChanges[depth] = Rml.bestMoveChanges;
+ // Send PV line to GUI and to log file
+ for (int i = 0; i < Min(UCIMultiPV, (int)Rml.size()); i++)
+ cout << Rml[i].pv_info_to_uci(pos, depth, alpha, beta, i) << endl;
+
if (UseLogFile)
LogFile << pretty_pv(pos, depth, value, current_search_time(), Rml[0].pv) << endl;
}
}
- *ponderMove = Rml[0].pv[1];
+ // When playing with strength handicap choose best move among the MultiPV set
+ // using a statistical rule dependent on SkillLevel. Idea by Heinz van Saanen.
+ if (SkillLevel < 20)
+ {
+ assert(MultiPV > 1);
+
+ // Rml list is already sorted by pv_score in descending order
+ int s;
+ int max_s = -VALUE_INFINITE;
+ int size = Min(MultiPV, (int)Rml.size());
+ int max = Rml[0].pv_score;
+ int var = Min(max - Rml[size - 1].pv_score, PawnValueMidgame);
+ int wk = 120 - 2 * SkillLevel;
+
+ // PRNG sequence should be non 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,
+ // then we choose the move with the resulting highest score.
+ for (int i = 0; i < size; i++)
+ {
+ s = Rml[i].pv_score;
+
+ // Don't allow crazy blunders even at very low skills
+ if (i > 0 && Rml[i-1].pv_score > s + EasyMoveMargin)
+ break;
+
+ // This is our magical formula
+ s += ((max - s) * wk + var * (RK.rand<unsigned>() % wk)) / 128;
+
+ if (s > max_s)
+ {
+ max_s = s;
+ bestMove = Rml[i].pv[0];
+ *ponderMove = Rml[i].pv[1];
+ }
+ }
+ }
+
return bestMove;
}
if (abs(ttValue) < VALUE_KNOWN_WIN)
{
- Value b = ttValue - depth;
+ Value b = ttValue - int(depth);
ss->excludedMove = move;
ss->skipNullMove = true;
Value v = search<NonPV>(pos, ss, b - 1, b, depth / 2, ply);