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zbot.py
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zbot.py
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import chess
import random
import utils
import math
from time import time
MINUS_INF = -math.inf
POS_INF = math.inf
def timer_func(func):
# This function shows the execution time of
# the function object passed
def wrap_func(*args, **kwargs):
t1 = time()
result = func(*args, **kwargs)
t2 = time()
print(f'Function {func.__name__!r} executed in {(t2-t1):.4f}s')
return result
return wrap_func
class node():
def __init__(self, eval, depth):
self.eval = eval
self.depth = depth
class Zbot():
def __init__(self, mode = "random", depth = 5, w = [20, 2, 1, 8]):
""" features = [material, activity, enemy_king, king_safety]
"""
self.mode = mode
self.table = {}
self.depth = depth
self.win = 0
self.w = w
def get_move(self, board):
if self.mode == "random":
return self.get_move_random(board)
elif self.mode == "minimax":
return self.get_move_minimax(board)
elif self.mode == "genetic":
return self.get_move_genetic(board)
def get_move_random(self, board):
moves = [m for m in board.legal_moves]
if len(moves) > 0:
return moves[random.randrange(0, len(moves))]
# utility function for minimax
def utility(self, board):
B = utils.to_string(str(board))
w = self.w
# material advantage
material = utils.material_count(B)
# activity of pieces
activity = 0
activity = utils.pieces_forward(B, board.turn)
# how close enemy king is to edge of board for checkmate
enemy_king = 0
if board.fullmove_number > 40:
opponent = chess.WHITE if board.turn == chess.BLACK else chess.BLACK
x, y = utils.get_king(B, opponent)
enemy_king = utils.away_from_center((x, y)) if board.turn == chess.WHITE else -utils.away_from_center((x, y))
enemy_king *= board.fullmove_number
# king safety
king_safety = 0
if board.fullmove_number < 15:
king_safety = utils.king_safety(B, board.turn)
features = [material, activity, enemy_king, king_safety]
eval = sum([w[i] * features[i] for i in range(len(features))])
return eval
@timer_func
def get_move_minimax(self, board):
depth = self.depth
global nodes
nodes = 0
def maxi(board, d, alpha, beta):
global nodes
nodes += 1
outcome = board.outcome()
non_quiet_moves, rest = utils.get_sorted_legal_moves(board.copy())
if outcome != None:
if outcome.termination == chess.Termination.CHECKMATE:
if outcome.winner == chess.BLACK:
return None, MINUS_INF
elif outcome.winner == chess.WHITE:
return None, POS_INF
else:
return None, 0
if d == 0 and non_quiet_moves == []:
return None, self.utility(board)
best_eval = MINUS_INF
best_move = None
search_moves = non_quiet_moves + rest if d >= 0 else non_quiet_moves
for m in search_moves:
# for m in board.legal_moves:
board.push(m)
move, move_eval = mini(board, d-1, alpha, beta)
if move_eval > best_eval:
best_eval = move_eval
best_move = m
board.pop()
if best_eval >= beta:
return best_move, best_eval
if best_eval > alpha:
alpha = best_eval
return best_move, best_eval
def mini(board, d, alpha, beta):
global nodes
nodes += 1
outcome = board.outcome()
non_quiet_moves, rest = utils.get_sorted_legal_moves(board.copy())
if outcome != None:
if outcome.termination == chess.Termination.CHECKMATE:
if outcome.winner == chess.BLACK:
return None, MINUS_INF
elif outcome.winner == chess.WHITE:
return None, POS_INF
else:
return None, 0
if d == 0 and non_quiet_moves == []:
return None, self.utility(board)
best_eval = POS_INF
best_move = None
search_moves = non_quiet_moves + rest if d >= 0 else non_quiet_moves
for m in search_moves:
# for m in board.legal_moves:
board.push(m)
move, move_eval = maxi(board, d-1, alpha, beta)
if move_eval < best_eval:
best_eval = move_eval
best_move = m
board.pop()
if best_eval <= alpha:
return best_move, best_eval
if best_eval < beta:
beta = best_eval
return best_move, best_eval
if board.turn == chess.WHITE:
move, eval = maxi(board, d = depth, alpha = MINUS_INF, beta = POS_INF)
print(nodes)
if move != None:
return move
else:
return self.get_move_random(board)
elif board.turn == chess.BLACK:
move, eval = mini(board, d = depth, alpha = MINUS_INF, beta = POS_INF)
print(nodes)
if move != None:
return move
else:
return self.get_move_random(board)