import copy from collections import deque class Strict3x3GreedyCollector: """ 严格的3x3视野贪心资源收集器 每次移动时只考虑3x3视野范围内的资源 如果视野内没有资源，则随机移动探索 """ def __init__(self, maze, start_pos=None, end_pos=None): """初始化收集器""" self.original_maze = copy.deepcopy(maze) self.maze = copy.deepcopy(maze) self.rows = len(maze) self.cols = len(maze[0]) if self.rows > 0 else 0 # 寻找起始位置和目标位置 self.start_pos = start_pos or self._find_position('s') self.end_pos = end_pos or self._find_position('e') if not self.start_pos: raise ValueError("无法找到起始位置 's'") if not self.end_pos: raise ValueError("无法找到目标位置 'e'") self.current_pos = self.start_pos self.path = [self.start_pos] self.collected_resources = [] self.total_value = 0 self.visited_resources = set() self.explored_positions = set([self.start_pos]) print(f"严格3x3视野模式") print(f"起始位置: {self.start_pos}") print(f"目标位置: {self.end_pos}") def _find_position(self, target): """寻找地图中指定字符的位置""" for i in range(self.rows): for j in range(self.cols): if self.maze[i][j].lower() == target.lower(): return (i, j) return None def get_3x3_vision(self, pos): """获取以pos为中心的3x3视野范围内的所有单元格""" row, col = pos vision = {} # 遍历3x3范围 for dr in range(-1, 2): for dc in range(-1, 2): new_row, new_col = row + dr, col + dc # 检查边界 if 0 <= new_row < self.rows and 0 <= new_col < self.cols: vision[(new_row, new_col)] = self.maze[new_row][new_col] return vision def get_adjacent_cells(self, pos): """获取当前位置的上下左右四个相邻位置""" row, col = pos adjacent = [] # 上下左右四个方向 directions = [(-1, 0), (1, 0), (0, -1), (0, 1)] for dr, dc in directions: new_row, new_col = row + dr, col + dc # 检查边界和可移动性 if (0 <= new_row < self.rows and 0 <= new_col < self.cols and self.can_move_to((new_row, new_col))): adjacent.append((new_row, new_col)) return adjacent def can_move_to(self, pos): """检查是否可以移动到指定位置""" row, col = pos cell = self.maze[row][col] # 不能移动到墙壁 return cell != '1' def evaluate_resource_value(self, cell): """评估资源的价值""" if cell.startswith('g'): try: return int(cell[1:]) except ValueError: return 0 elif cell.startswith('t'): try: return -int(cell[1:]) except ValueError: return 0 else: return 0 def find_best_resource_in_3x3_vision(self): """ 严格在3x3视野范围内找到价值最高的资源 Returns: tuple: (最佳资源位置, 资源价值) 或 (None, 0) """ vision = self.get_3x3_vision(self.current_pos) best_pos = None best_value = float('-inf') for pos, cell in vision.items(): # 跳过已访问的资源 if pos in self.visited_resources: continue # 跳过当前位置 if pos == self.current_pos: continue # 跳过不可移动的位置 if not self.can_move_to(pos): continue # 检查是否可以直接到达（相邻位置） if pos not in self.get_adjacent_cells(self.current_pos): continue # 检查是否为资源 value = self.evaluate_resource_value(cell) if value != 0 and value > best_value: best_value = value best_pos = pos return best_pos, best_value if best_pos else 0 def find_exploration_target(self): """ 当视野内没有资源时，寻找探索目标 优先选择未探索过的位置 """ adjacent = self.get_adjacent_cells(self.current_pos) # 优先选择未探索的位置 unexplored = [pos for pos in adjacent if pos not in self.explored_positions] if unexplored: return unexplored[0] # 选择第一个未探索的位置 # 如果所有相邻位置都探索过，选择任意一个 if adjacent: return adjacent[0] return None def collect_resource(self, pos): """收集指定位置的资源""" row, col = pos cell = self.maze[row][col] value = self.evaluate_resource_value(cell) if value != 0: self.collected_resources.append({ 'position': pos, 'type': cell, 'value': value }) self.total_value += value self.visited_resources.add(pos) print(f"收集资源: 位置{pos}, 类型{cell}, 价值{value}, 总价值{self.total_value}") def run_strict_3x3_collection(self, max_moves=1000): """ 运行严格3x3视野贪心资源收集算法 Args: max_moves: 最大移动步数，防止无限循环 Returns: dict: 包含路径、收集的资源等信息 """ print("\\n开始严格3x3视野贪心资源收集...") moves = 0 stuck_count = 0 # 连续无法找到资源的次数 max_stuck = 20 # 最大连续无资源次数 while moves < max_moves and stuck_count < max_stuck: moves += 1 # 在3x3视野内寻找最佳资源 best_resource_pos, best_value = self.find_best_resource_in_3x3_vision() if best_resource_pos is not None: print(f"第{moves}步: 发现视野内资源 位置{best_resource_pos}, 价值{best_value}") # 移动到资源位置并收集 self.current_pos = best_resource_pos self.path.append(best_resource_pos) self.explored_positions.add(best_resource_pos) self.collect_resource(best_resource_pos) stuck_count = 0 # 重置无资源计数 else: # 视野内没有资源，进行探索性移动 exploration_target = self.find_exploration_target() if exploration_target: print(f"第{moves}步: 视野内无资源，探索移动到 {exploration_target}") self.current_pos = exploration_target self.path.append(exploration_target) self.explored_positions.add(exploration_target) stuck_count += 1 else: print(f"第{moves}步: 无法进行任何移动，结束收集") break if moves >= max_moves: print(f"达到最大移动步数 {max_moves}，结束收集") elif stuck_count >= max_stuck: print(f"连续 {max_stuck} 步未找到资源，结束收集") print("严格3x3视野资源收集完成！") return self.get_collection_result() def get_collection_result(self): """获取收集结果""" return { 'path': self.path.copy(), 'collected_resources': self.collected_resources.copy(), 'total_value': self.total_value, 'total_moves': len(self.path) - 1, 'resources_count': len(self.collected_resources), 'start_pos': self.start_pos, 'end_pos': self.end_pos, 'final_pos': self.current_pos, 'explored_positions': len(self.explored_positions) } def print_result_summary(self): """打印收集结果摘要""" result = self.get_collection_result() print("\\n=== 严格3x3视野贪心收集结果摘要 ===") print(f"起始位置: {result['start_pos']}") print(f"最终位置: {result['final_pos']}") print(f"总移动步数: {result['total_moves']}") print(f"探索位置数: {result['explored_positions']}") print(f"收集资源数量: {result['resources_count']}") print(f"资源总价值: {result['total_value']}") print("\\n收集的资源详情:") for i, resource in enumerate(result['collected_resources'], 1): print(f" {i}. 位置{resource['position']}: {resource['type']} (价值: {resource['value']})") # 显示路径的关键点 path_points = result['path'] if len(path_points) <= 10: path_str = ' -> '.join(map(str, path_points)) else: path_str = f"{path_points[0]} -> ... -> {path_points[-1]} (共{len(path_points)}个位置)" print(f"\\n移动路径: {path_str}") def visualize_path_on_maze(self): """在迷宫上可视化移动路径""" visual_maze = copy.deepcopy(self.original_maze) # 标记路径 for i, pos in enumerate(self.path): row, col = pos if pos == self.start_pos: visual_maze[row][col] = 'S' # 起点 elif pos in [r['position'] for r in self.collected_resources]: # 已收集的资源位置 visual_maze[row][col] = '*' elif i == len(self.path) - 1: # 最终位置 visual_maze[row][col] = 'F' else: # 路径点 visual_maze[row][col] = '.' return visual_maze def print_visual_maze(self): """打印可视化的迷宫""" visual_maze = self.visualize_path_on_maze() print("\\n=== 严格3x3视野路径可视化迷宫 ===") print("S: 起点, F: 终点, *: 已收集资源, .: 路径") for row in visual_maze: print(' '.join(f"{cell:>2}" for cell in row)) def compare_algorithms(): """比较不同算法的效果""" # 创建一个更大的示例迷宫 demo_maze = [ ['s', '0', 'g5', '1', 't3', '0', 'g8'], ['0', '1', '0', '0', 'g2', '1', '0'], ['g3', '0', '1', 't2', '0', '0', 'g6'], ['0', 't1', '0', '0', 'g4', '1', '0'], ['1', '0', 'g1', '0', '0', '0', 't5'], ['0', 'g7', '0', '1', '0', 'g9', '0'], ['t4', '0', '0', '0', '1', '0', 'e'] ] print("=== 算法比较演示 ===") print("迷宫说明:") print(" s: 起点, e: 终点") print(" g数字: 金币资源 (正收益)") print(" t数字: 陷阱资源 (负收益)") print(" 0: 可通行路径, 1: 墙壁") print("\\n原始迷宫:") for row in demo_maze: print(' '.join(f"{cell:>2}" for cell in row)) print("\\n" + "="*60) print("严格3x3视野贪心算法:") print("="*60) # 运行严格3x3视野算法 strict_collector = Strict3x3GreedyCollector(demo_maze) strict_result = strict_collector.run_strict_3x3_collection() strict_collector.print_result_summary() strict_collector.print_visual_maze() return strict_collector, strict_result if __name__ == "__main__": # 运行比较演示 strict_collector, strict_result = compare_algorithms()