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