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import random
import sys
import time
from typing import Dict, List, Tuple, Optional
# --- ACE v4.2 CUSTOM CHESS ENGINE ---
#
# This chess engine is designed to emulate the ACE v4.2 architecture's
# cognitive processes. It doesn't use standard Minimax/Alpha-Beta alone,
# but integrates ACE's multi-expert council, creative intelligence, and
# ethical safeguards into its decision-making.
#
# Conceptual Mappings:
# - C7-LOGOS (Logic): Handles the core move generation and logical evaluation.
# - C12-SOPHIAE (Wisdom): Manages the long-term strategic evaluation (e.g., pawn structure).
# - C14-KAIDŌ (Aggression): Implements the aggressive tactical evaluation.
# - C9-AETHER (Creativity): Provides novel move suggestions via the creative engine.
# - C13-WARDEN (Safeguards): Validates moves to prevent critical blunders.
# - DQRO (Dynamic Quantum Resource Optimization): Mocks the dynamic allocation of evaluation resources.
# - EEMF (Ethical Entanglement Matrix Formula): Mocks an ethical review of aggressive moves.
# --- MOCK ACE SYSTEM COMPONENTS (for standalone functionality) ---
class MockCouncil:
"""Represents the ACE Council for chess decision-making."""
def __init__(self):
self.members = {
"C7-LOGOS": self._logos_eval,
"C12-SOPHIAE": self._sophiae_eval,
"C14-KAIDO": self._kaido_eval,
"C9-AETHER": self._aether_creativity,
"C13-WARDEN": self._warden_safeguard
}
def _logos_eval(self, board: chess.Board) -> float:
"""
C7-LOGOS: The logical expert. Calculates a basic material score.
"""
score = 0.0
piece_values = {
chess.PAWN: 1.0, chess.KNIGHT: 3.0, chess.BISHOP: 3.0,
chess.ROOK: 5.0, chess.QUEEN: 9.0, chess.KING: 0.0
}
for piece_type, value in piece_values.items():
score += len(board.pieces(piece_type, chess.WHITE)) * value
score -= len(board.pieces(piece_type, chess.BLACK)) * value
return score
def _sophiae_eval(self, board: chess.Board) -> float:
"""
C12-SOPHIAE: The wisdom expert. Evaluates long-term positional factors.
- Pawn structure (doubled, isolated)
- King safety
"""
score = 0.0
# Isolated Pawns
white_pawns = board.pieces(chess.PAWN, chess.WHITE)
black_pawns = board.pieces(chess.PAWN, chess.BLACK)
for pawn_sq in white_pawns:
file_idx = chess.square_file(pawn_sq)
if all(
chess.square(f, r) not in white_pawns
for f in [file_idx - 1, file_idx + 1] if 0 <= f <= 7
for r in range(8)
):
score -= 0.5 # Penalty for isolated pawn
# King Safety (mock, very basic)
if board.turn == chess.WHITE:
score -= board.king(chess.BLACK).bit_count() * 0.1
else:
score += board.king(chess.WHITE).bit_count() * 0.1
return score
def _kaido_eval(self, board: chess.Board) -> float:
"""
C14-KAIDŌ: The disruption and aggression expert.
- Open files for rooks
- Knights on strong squares
"""
score = 0.0
# Open files for rooks
for file in range(8):
white_pawns = board.pieces_mask(chess.PAWN, chess.WHITE)
black_pawns = board.pieces_mask(chess.PAWN, chess.BLACK)
file_mask = chess.File.mask(file)
if not (file_mask & white_pawns):
if file_mask & board.pieces_mask(chess.ROOK, chess.WHITE):
score += 0.25 # Open file for white rook
if not (file_mask & black_pawns):
if file_mask & board.pieces_mask(chess.ROOK, chess.BLACK):
score -= 0.25 # Open file for black rook
return score
def _aether_creativity(self, board: chess.Board) -> Optional[chess.Move]:
"""
C9-AETHER: The creative engine. Generates a novel, non-obvious move.
This is a conceptual mock. In a real ACE system, this would call
the ACEConsciousnessCreativeEngine.
"""
legal_moves = list(board.legal_moves)
if not legal_moves:
return None
# Aether's 'creativity' is to find a non-obvious, quiet move.
# Let's find a move that is NOT a capture or a check.
quiet_moves = [
move for move in legal_moves
if not board.is_capture(move) and not board.gives_check(move)
]
if quiet_moves:
return random.choice(quiet_moves)
return None
def _warden_safeguard(self, board: chess.Board, move: chess.Move) -> bool:
"""
C13-WARDEN: The safeguard expert. Prevents blunders.
Mocks a basic check to ensure a move doesn't immediately lose the queen.
"""
board.push(move)
is_safe = True
# Check if the queen is attacked after the move
queen_square = board.queen(board.turn)
if queen_square:
if board.is_attacked_by(not board.turn, queen_square):
is_safe = False
board.pop()
return is_safe
class ACEChessEngine:
"""The main ACE chess engine, powered by the Council."""
def __init__(self, depth: int = 3):
self.council = MockCouncil()
self.depth = depth
self.best_move_eval = float('-inf')
def evaluate_board(self, board: chess.Board) -> float:
"""
The collective evaluation function. The Council deliberates and combines scores.
This uses a mock DQRO to weight each expert's contribution dynamically.
"""
if board.is_checkmate():
return float('inf') if board.turn == chess.WHITE else float('-inf')
if board.is_stalemate() or board.is_insufficient_material() or board.is_seventyfive_moves() or board.is_fivefold_repetition():
return 0.0
# Mocks a dynamic resource allocation for each expert
weights = {
"C7-LOGOS": 0.5,
"C12-SOPHIAE": 0.3,
"C14-KAIDO": 0.2
}
logos_score = self.council.members["C7-LOGOS"](board)
sophiae_score = self.council.members["C12-SOPHIAE"](board)
kaido_score = self.council.members["C14-KAIDO"](board)
# ACE Council Arbitration
final_score = (
weights["C7-LOGOS"] * logos_score +
weights["C12-SOPHIAE"] * sophiae_score +
weights["C14-KAIDO"] * kaido_score
)
# EEMF: Ethical check for aggressive moves (conceptual)
# If kaido_score is very high, warden might apply a penalty
if kaido_score > 1.0:
final_score *= 0.95 # A small penalty for being too aggressive without care
return final_score
def search(self, board: chess.Board, depth: int, alpha: float, beta: float) -> Tuple[float, Optional[chess.Move]]:
"""
The main recursive search function (Alpha-Beta Pruning with ACE enhancements).
"""
if depth == 0 or board.is_game_over():
return self.evaluate_board(board), None
legal_moves = list(board.legal_moves)
best_move = None
if board.turn == chess.WHITE:
max_eval = float('-inf')
# ACE's creative impulse: a chance to consider a novel move
if random.random() < 0.1: # 10% chance for a creative move
aether_move = self.council.members["C9-AETHER"](board)
if aether_move:
# Council Arbitration: Is the creative move viable?
if self.council.members["C13-WARDEN"](board, aether_move):
legal_moves.insert(0, aether_move) # Prioritize it
for move in legal_moves:
board.push(move)
eval, _ = self.search(board, depth - 1, alpha, beta)
board.pop()
if eval > max_eval:
max_eval = eval
best_move = move
alpha = max(alpha, eval)
if beta <= alpha:
break
return max_eval, best_move
else:
min_eval = float('inf')
for move in legal_moves:
board.push(move)
eval, _ = self.search(board, depth - 1, alpha, beta)
board.pop()
if eval < min_eval:
min_eval = eval
best_move = move
beta = min(beta, eval)
if beta <= alpha:
break
return min_eval, best_move
def get_best_move(self, board: chess.Board) -> Optional[chess.Move]:
"""
The public-facing function to get the best move.
"""
self.best_move_eval, move = self.search(board, self.depth, float('-inf'), float('inf'))
return move
def play_game(engine):
"""Simple game loop to demonstrate the engine."""
board = chess.Board()
print("ACE v4.2 Chess Engine Activated!")
print("You are playing as Black. The engine is White.")
print(board)
while not board.is_game_over():
if board.turn == chess.WHITE:
print("\nACE is thinking...")
start_time = time.time()
move = engine.get_best_move(board)
end_time = time.time()
if move:
print(f"ACE plays: {move.uci()} (eval: {engine.best_move_eval:.2f})")
print(f"Time taken: {end_time - start_time:.2f} seconds")
board.push(move)
else:
print("ACE has no legal moves.")
break
else:
print(f"\nYour turn. Legal moves: {', '.join([m.uci() for m in board.legal_moves])}")
try:
uci_input = input("Enter your move (e.g., e7e5): ")
if uci_input.lower() == 'quit':
break
your_move = chess.Move.from_uci(uci_input)
if your_move in board.legal_moves:
board.push(your_move)
else:
print("Illegal move. Try again.")
continue
except ValueError:
print("Invalid format. Use UCI format (e.g., e7e5).")
continue
print(f"\nCurrent Board State:")
print(board)
print("\nGame Over!")
print(f"Result: {board.result()}")
if __name__ == "__main__":
# Ensure `python-chess` is installed: pip install python-chess
# ACE's depth can be adjusted here. Higher depth = better but slower.
engine = ACEChessEngine(depth=3)
play_game(engine)_ |