Add MVV-LVA capture ordering, check extensions, and delta pruning

moonfish/engines/alpha_beta.py

@@ -5,7 +5,7 @@
 from moonfish.config import Config
 from moonfish.engines.random import choice
 from moonfish.move_ordering import organize_moves, organize_moves_quiescence
-from moonfish.psqt import board_evaluation, count_pieces
+from moonfish.psqt import MG_PIECE_VALUES, board_evaluation, count_pieces
 
 CACHE_KEY = dict[
     tuple[object, int, bool, float, float], tuple[float | int, Move | None]
@@ -15,6 +15,10 @@
 NEG_INF = float("-inf")
 NULL_MOVE = Move.null()
 
+# Maximum possible capture gain for delta pruning in quiescence
+# Queen value is the largest possible single capture
+DELTA_MARGIN = MG_PIECE_VALUES[5] + 200  # queen value + safety margin
+
 
 class AlphaBeta:
     """
@@ -132,6 +136,11 @@ def quiescence_search(
             if stand_pat >= beta:
                 return beta
 
+            # Delta pruning: if even the best possible capture can't improve alpha,
+            # there's no point searching further
+            if stand_pat + DELTA_MARGIN < alpha:
+                return alpha
+
             # Use stand-pat as baseline (we can always choose not to capture)
             best_score = stand_pat
             alpha = max(alpha, stand_pat)
@@ -266,9 +275,13 @@ def negamax(
             # make the move
             board.push(move)
 
+            # Check extension: if the move puts the opponent in check,
+            # extend the search by 1 ply to resolve the tactical situation
+            extension = 1 if board.is_check() else 0
+
             board_score = -self.negamax(
                 board,
-                depth - 1,
+                depth - 1 + extension,
                 null_move,
                 cache,
                 -beta,

moonfish/move_ordering.py

@@ -2,15 +2,24 @@
 
 from chess import BLACK, Board, Move
 
-from moonfish.psqt import evaluate_capture, evaluate_piece, get_phase
+from moonfish.psqt import (
+    MG_PIECE_VALUES,
+    evaluate_capture,
+    evaluate_piece,
+    get_phase,
+)
+
+# Simple integer piece values for fast MVV-LVA ordering in main search
+# Index by piece type: 0=None, 1=PAWN, 2=KNIGHT, 3=BISHOP, 4=ROOK, 5=QUEEN, 6=KING
+_MVV_LVA_VALUES = (0, 100, 300, 300, 500, 900, 10000)
 
 
 def organize_moves(board: Board):
     """
     This function receives a board and it returns a list of all the
     possible moves for the current player, sorted by importance.
-    It sends capturing moves at the starting positions in
-    the array (to try to increase pruning and do so earlier).
+    Captures are sorted by MVV-LVA (Most Valuable Victim - Least Valuable Attacker).
+    Promotions are prioritized. Non-captures are shuffled.
 
     Arguments:
             - board: chess board state
@@ -24,14 +33,37 @@ def organize_moves(board: Board):
     for move in board.legal_moves:
         if board.is_capture(move):
             captures.append(move)
+        elif move.promotion is not None:
+            # Promotions without capture — prioritize them
+            captures.append(move)
         else:
             non_captures.append(move)
 
-    random.shuffle(captures)
+    # Sort captures by MVV-LVA: highest victim value first, then lowest attacker
+    captures.sort(key=lambda m: _mvv_lva_score(board, m), reverse=True)
     random.shuffle(non_captures)
     return captures + non_captures
 
 
+def _mvv_lva_score(board: Board, move: Move) -> int:
+    """Fast integer MVV-LVA score for move ordering."""
+    if move.promotion is not None:
+        # Promotions get high score; queen promotion highest
+        return _MVV_LVA_VALUES[move.promotion] + 10000
+
+    # Victim value - attacker value (we want high victim, low attacker)
+    attacker = board.piece_type_at(move.from_square)
+    victim = board.piece_type_at(move.to_square)
+
+    if victim is None:
+        # En passant
+        return _MVV_LVA_VALUES[1] - _MVV_LVA_VALUES[1]  # pawn captures pawn
+
+    attacker_val = _MVV_LVA_VALUES[attacker] if attacker else 0
+    victim_val = _MVV_LVA_VALUES[victim] if victim else 0
+    return victim_val * 10 - attacker_val
+
+
 def is_tactical_move(board: Board, move: Move) -> bool:
     """
     Check if a move is tactical (should be searched in quiescence).