能否提供一个详细的六子棋游戏程序代码示例，包括所有必要的函数和规则实现？

由于六子棋规则相对简单，这里我将给出一个非常基础的Python程序框架，使用了Minimax算法作为核心。完整的游戏代码会涉及到更多的细节，例如用户界面、图形化显示棋盘、错误检查等，但这个基础版本可以帮助理解算法的核心逻辑。

import numpy as np

# 定义棋盘大小
BOARD_SIZE = 15

# 棋盘表示
class Board:
    def __init__(self):
        self.board = np.zeros((BOARD_SIZE, BOARD_SIZE), dtype=int)

    # 根据坐标落子
    def place_stone(self, player, row, col):
        self.board[row][col] = player

    # 判断是否有连线获胜
    def check_win(self, player):
        win_conditions = [(0, 1, 2), (3, 4, 5), (6, 7, 8), (9, 10, 11),
                          (12, 13, 14), (0, 3, 6), (1, 4, 7), (2, 5, 8),
                          (0, 12, 15), (1, 13, 14)]
        for condition in win_conditions:
            if all(self.board[row + c] == player for c in condition):
                return True
        return False

# Minimax函数
def minimax(board, player, max_depth=5):
    if board.check_win(player):
        return -1 if player == 1 else 1   # 胜利得正分，失败得负分
    elif not any(row.any() for row in board.board):   # 平局
        return 0
    elif max_depth == 0 or np.all(board.board == 0):   # 深度达到或棋盘为空
        return evaluate(board)
    
    # 假设是最大化得分
    if player == 1:
        value = -np.inf
        for next_row, next_col in get_valid_moves(board):
            new_board = Board.from_matrix(board.board.copy())
            new_board.place_stone(1, next_row, next_col)
            value = max(value, minimax(new_board, 2, max_depth - 1))
        return value

    # 假设是最大化得分，对手是2
    else:
        value = np.inf
        for next_row, next_col in get_valid_moves(board):
            new_board = Board.from_matrix(board.board.copy())
            new_board.place_stone(2, next_row, next_col)
            value = min(value, minimax(new_board, 1, max_depth - 1))
        return value

# 得到合法移动
def get_valid_moves(board):
    valid_moves = []
    for row in range(BOARD_SIZE):
        for col in range(BOARD_SIZE):
            if board.board[row][col] == 0:
                valid_moves.append((row, col))
    return valid_moves

# 评价函数
def evaluate(board):
    # 实际上需要根据实际规则进行评估，这里简化为均匀分布
    return sum(sum(board.board))

# 主游戏循环
def play():
    game_board = Board()
    while not game_board.check_win(1) and not game_board.check_win(2):
        print(game_board)
        player = 1 if game_board.board[-1][-1] == 0 else 2
        row, col = input(f"Player {player}, enter your move (row, col): ").split(',')
        game_board.place_stone(player, int(row), int(col))
        winner = minimax(game_board, player)
        if winner != 0:
            print(f"Player {winner+1} wins!")
            break

play()

在这个代码中，玩家轮流输入他们的行和列，然后Minimax函数会决定下一个最好的动作。请注意，此代码只是一个简化的示例，实际应用中你可能还需要添加更多的细节和优化。