2 Stockfish, a UCI chess playing engine derived from Glaurung 2.1
3 Copyright (C) 2004-2023 The Stockfish developers (see AUTHORS file)
5 Stockfish is free software: you can redistribute it and/or modify
6 it under the terms of the GNU General Public License as published by
7 the Free Software Foundation, either version 3 of the License, or
8 (at your option) any later version.
10 Stockfish is distributed in the hope that it will be useful,
11 but WITHOUT ANY WARRANTY; without even the implied warranty of
12 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
13 GNU General Public License for more details.
15 You should have received a copy of the GNU General Public License
16 along with this program. If not, see <http://www.gnu.org/licenses/>.
19 #ifndef MOVEPICK_H_INCLUDED
20 #define MOVEPICK_H_INCLUDED
27 #include <type_traits> // IWYU pragma: keep
35 // StatsEntry stores the stat table value. It is usually a number but could
36 // be a move or even a nested history. We use a class instead of a naked value
37 // to directly call history update operator<<() on the entry so to use stats
38 // tables at caller sites as simple multi-dim arrays.
39 template<typename T, int D>
45 void operator=(const T& v) { entry = v; }
46 T* operator&() { return &entry; }
47 T* operator->() { return &entry; }
48 operator const T&() const { return entry; }
50 void operator<<(int bonus) {
51 assert(abs(bonus) <= D); // Ensure range is [-D, D]
52 static_assert(D <= std::numeric_limits<T>::max(), "D overflows T");
54 entry += (bonus * D - entry * abs(bonus)) / (D * 5 / 4);
56 assert(abs(entry) <= D);
60 // Stats is a generic N-dimensional array used to store various statistics.
61 // The first template parameter T is the base type of the array, and the second
62 // template parameter D limits the range of updates in [-D, D] when we update
63 // values with the << operator, while the last parameters (Size and Sizes)
64 // encode the dimensions of the array.
65 template<typename T, int D, int Size, int... Sizes>
66 struct Stats: public std::array<Stats<T, D, Sizes...>, Size> {
67 using stats = Stats<T, D, Size, Sizes...>;
69 void fill(const T& v) {
71 // For standard-layout 'this' points to the first struct member
72 assert(std::is_standard_layout_v<stats>);
74 using entry = StatsEntry<T, D>;
75 entry* p = reinterpret_cast<entry*>(this);
76 std::fill(p, p + sizeof(*this) / sizeof(entry), v);
80 template<typename T, int D, int Size>
81 struct Stats<T, D, Size>: public std::array<StatsEntry<T, D>, Size> {};
83 // In stats table, D=0 means that the template parameter is not used
92 // ButterflyHistory records how often quiet moves have been successful or
93 // unsuccessful during the current search, and is used for reduction and move
94 // ordering decisions. It uses 2 tables (one for each color) indexed by
95 // the move's from and to squares, see www.chessprogramming.org/Butterfly_Boards
97 using ButterflyHistory = Stats<int16_t, 7183, COLOR_NB, int(SQUARE_NB) * int(SQUARE_NB)>;
99 // CounterMoveHistory stores counter moves indexed by [piece][to] of the previous
100 // move, see www.chessprogramming.org/Countermove_Heuristic
101 using CounterMoveHistory = Stats<Move, NOT_USED, PIECE_NB, SQUARE_NB>;
103 // CapturePieceToHistory is addressed by a move's [piece][to][captured piece type]
104 using CapturePieceToHistory = Stats<int16_t, 10692, PIECE_NB, SQUARE_NB, PIECE_TYPE_NB>;
106 // PieceToHistory is like ButterflyHistory but is addressed by a move's [piece][to]
107 using PieceToHistory = Stats<int16_t, 29952, PIECE_NB, SQUARE_NB>;
109 // ContinuationHistory is the combined history of a given pair of moves, usually
110 // the current one given a previous one. The nested history table is based on
111 // PieceToHistory instead of ButterflyBoards.
113 using ContinuationHistory = Stats<PieceToHistory, NOT_USED, PIECE_NB, SQUARE_NB>;
116 // MovePicker class is used to pick one pseudo-legal move at a time from the
117 // current position. The most important method is next_move(), which returns a
118 // new pseudo-legal move each time it is called, until there are no moves left,
119 // when MOVE_NONE is returned. In order to improve the efficiency of the
120 // alpha-beta algorithm, MovePicker attempts to return the moves which are most
121 // likely to get a cut-off first.
130 MovePicker(const MovePicker&) = delete;
131 MovePicker& operator=(const MovePicker&) = delete;
132 MovePicker(const Position&,
135 const ButterflyHistory*,
136 const CapturePieceToHistory*,
137 const PieceToHistory**,
140 MovePicker(const Position&,
143 const ButterflyHistory*,
144 const CapturePieceToHistory*,
145 const PieceToHistory**,
147 MovePicker(const Position&, Move, Value, const CapturePieceToHistory*);
148 Move next_move(bool skipQuiets = false);
151 template<PickType T, typename Pred>
155 ExtMove* begin() { return cur; }
156 ExtMove* end() { return endMoves; }
159 const ButterflyHistory* mainHistory;
160 const CapturePieceToHistory* captureHistory;
161 const PieceToHistory** continuationHistory;
163 ExtMove refutations[3], *cur, *endMoves, *endBadCaptures;
165 Square recaptureSquare;
168 ExtMove moves[MAX_MOVES];
171 } // namespace Stockfish
173 #endif // #ifndef MOVEPICK_H_INCLUDED