#BFS算法node
###1.走迷宫的最短路径 问题: 给出一个起点和终点, 求起点走到终点的最短距离.
思路: 每层节点为4^n的树, 搜到符合结果的节点便可.
起点(0,0) 终点(4,4) 1为墙(不可走)
python codepython
from queue import Queue M = [ [0, 0, 1, 0, 0], [0, 0, 0, 0, 0], [0, 1, 1, 1, 0], [0, 1, 0, 0, 0], [0, 0, 0, 1, 0], ] V = [[False for j in range(5)] for i in range(5)] dx = [-1, 1, 0, 0] dy = [ 0, 0, -1, 1] class Node: def __init__(self, x, y, step): self.x, self.y, self.step = x, y, step def bfs(start_x, start_y): que = Queue() que.put(Node(start_x, start_y, 0)) while not que.empty(): node = que.get() x, y, step = node.x, node.y, node.step for i in range(4): nx, ny = x+dx[i], y+dy[i] if nx<0 or ny<0 or nx>4 or ny>4: continue if V[nx][ny] or M[nx][ny]==1: continue if nx==4 and ny==4: return step+1 que.put(Node(nx, ny, step+1)) V[nx][ny] = True ans = bfs(0, 0) print(ans)
###2.八数码(九宫问题) 问题: 3×3棋盘上有1~8的数字和一个空格, 每次移动空格能够和相邻数字交换,给出一个初始状态和一个目标状态, 找出最少的移动步骤.
思路: 同走迷宫, 中途产生的状态处理比以前麻烦一点.算法
须要把已经出现过的状态记录在集合中, 防止重复树节点致使搜索树进行不下去.
python不支持将列表放在集合中,用技巧进行转换, 存整数.
python code函数
from queue import Queue import copy M = [ [0, 8, 7], [6, 5, 4], [3, 2, 1] ] T = [ [1, 2, 3], [4, 5, 6], [7, 8, 0] ] S = set() dx = [-1, 1, 0, 0] dy = [ 0, 0, -1, 1] class Node: def __init__(self, x, y, stat, step): self.x, self.y = x, y self.stat, self.step = stat, step def calc_value(stat): weight, sum = 1, 0 for i in range(3): for j in range(3): sum += stat[i][j]*weight weight *= 10 return sum def bfs(): que = Queue() start_node = Node(0, 0, copy.deepcopy(M), 0) que.put(start_node) while not que.empty(): node = que.get() x, y = node.x, node.y stat, step = node.stat, node.step S.add(calc_value(stat)) for i in range(0, 4): nx, ny = x+dx[i], y+dy[i] if nx<0 or ny<0 or nx>2 or ny>2: continue new_stat = copy.deepcopy(stat) new_stat[nx][ny], new_stat[x][y] = new_stat[x][y], new_stat[nx][ny] if calc_value(new_stat) in S: continue if new_stat == T: return step+1 que.put(Node(nx, ny, new_stat, step+1)) ans = bfs() print(ans)
能够在生成状态前先计算value, 不过提高的速度很少.
再增长一个类属性last_node来连接上一个状态, 打印倒着的变化过程.
python codecode
from queue import Queue import copy M = [ [0, 8, 7], [6, 5, 4], [3, 2, 1] ] T = [ [1, 2, 3], [4, 5, 6], [7, 8, 0] ] S = set() dx = [-1, 1, 0, 0] dy = [ 0, 0, -1, 1] class Node: def __init__(self, x, y, stat, step, last_node): self.x, self.y = x, y self.stat, self.step = stat, step self.last_node = last_node def calc_value(stat): weight, sum = 1, 0 for i in range(3): for j in range(3): sum += stat[i][j]*weight weight *= 10 return sum def swap_stat(stat, x, y, nx, ny): stat[x][y], stat[nx][ny] = stat[nx][ny], stat[x][y] def bfs(): que = Queue() start_node = Node(0, 0, M, 0, None) que.put(start_node) while not que.empty(): node = que.get() x, y = node.x, node.y stat, step = node.stat, node.step S.add(calc_value(stat)) for i in range(0, 4): nx, ny = x+dx[i], y+dy[i] if nx<0 or ny<0 or nx>2 or ny>2: continue swap_stat(stat, x, y, nx, ny) if calc_value(stat) in S: swap_stat(stat, x, y, nx, ny) continue if stat == T: return step+1, node new_stat = copy.deepcopy(stat) swap_stat(stat, x, y, nx, ny) que.put(Node(nx, ny, new_stat, step+1, node)) ans, node = bfs() print(ans) while node.last_node != None: print(node.stat) node = node.last_node
###优先队列BFS 依然是走迷宫, 不过此次判断的是最短期 增长三秒(遇到2), 因此最优不是那条路.队列
from queue import PriorityQueue M = [ [0, 0, 1, 0, 0], [0, 0, 0, 0, 0], [0, 1, 1, 1, 2], [0, 1, 0, 0, 0], [0, 0, 0, 1, 0] ] V = [[False for j in range(5)] for i in range(5)] dx = [-1, 1, 0, 0] dy = [ 0, 0, -1, 1] class Node: def __init__(self, x, y, step, time): self.x, self.y = x, y self.step, self.time = step, time def __lt__(self, other): if self.time > other.time: return True return False def bfs(start_x, start_y): que = PriorityQueue() que.put(Node(start_x, start_y, 0, 0)) while not que.empty(): node = que.get() x, y = node.x, node.y step, time = node.step, node.time for i in range(4): nx, ny = x+dx[i], y+dy[i] if nx<0 or ny<0 or nx>4 or ny>4: continue if V[nx][ny] or M[nx][ny]==1: continue if nx==4 and ny==4: return time+1 t = V[nx][ny]+1 que.put(Node(nx, ny, step+1, time+t)) V[nx][ny] = True ans = bfs(0, 0) print(ans)
###三维立方体迷宫BFS的解法 多增长几个方向, 在类中多增长一个成员z, 对应修改bfs函数便可.get
dx = [0, 0, 1, 0, 0, -1] dy = [0, 1, 0, 0, -1, 0] dz = [1, 0, 0, -1, 0, 0] class Node: def __init__(self, x, y, z, step): self.x, self.y, self.z, self.step = x, y, z, step