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#人工智障
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import time
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import pygame
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import random
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import map_game
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import button_event
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from map_config import *
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from button import *
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import copy
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import math
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import AI_map #AI专用地图
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import sound
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#导入win32api 用于弹出窗口
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import win32api,win32con
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from search_result import *
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lastTime = int(time.time()*1000)
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game_state = 0 #0为手动 1为AI
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#0左 1右 2上 3下
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def ai_find_direction():
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#dir = random.randint(0,3) #人工智障1.0 随机数生成
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dir = lanmeng() #人工智障2.0 (贪心算法)
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#dir = lanmeng2() #人工智障3.0 (minimax算法 但经过试验 效果比2.0还要差 而且速度很慢所以放弃)
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return dir
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#AI继续启动吧
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def ai_2048_game_going(speed = 500):
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global lastTime
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global game_state
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if map_game.judge_gameover() == False and map_game.judge_gamewin() == False:
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#map_game.sound_flag = 0
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for event in pygame.event.get():
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#按钮事件检测
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button_event.buttonBase.check_event(event)
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button_event.buttonReturn.check_event(event)
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button_event.buttonAI.check_event(event)
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button_event.buttonTips.check_event(event)
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button_event.buttonReshow.check_event(event)
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if event.type == pygame.KEYDOWN:
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if(event.key == pygame.K_z):#Z键加快速度
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if map_game.ai_delay_time > 50:
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map_game.ai_delay_time = map_game.ai_delay_time - 50
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if(event.key == pygame.K_x):#X键减慢速度
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if map_game.ai_delay_time < 1000:
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map_game.ai_delay_time = map_game.ai_delay_time + 50
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thisTime = int(time.time()*1000)
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if thisTime - lastTime > speed:
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lastTime = int(time.time()*1000)
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dir = ai_find_direction()
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if dir == 0:
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map_game.go_move_left()
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elif dir == 1:
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map_game.go_move_right()
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elif dir == 2:
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map_game.go_move_up()
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elif dir == 3:
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map_game.go_move_down()
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else:
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game_state = 0 #跑不了了 你爱咋整咋整
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else:
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game_state = 0
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for event in pygame.event.get():
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#按钮事件检测
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button_event.buttonBase.check_event(event)
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button_event.buttonReturn.check_event(event)
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button_event.buttonAI.check_event(event)
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button_event.buttonTips.check_event(event)
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button_event.buttonReshow.check_event(event)
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ii = 1
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reshow_temp_buf = [ #缓存 记录
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[0,0,0,0],
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[0,0,0,0],
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[0,0,0,0],
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[0,0,0,0]
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]
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lstTime = int(time.time()*1000)
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#回放模式
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def reshow_mode(delaytime):
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global ii
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global lstTime
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global game_state
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tisTime = int(time.time()*1000)
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for event in pygame.event.get():
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#按钮事件检测
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button_event.buttonBase.check_event(event)
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button_event.buttonReturn.check_event(event)
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button_event.buttonAI.check_event(event)
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button_event.buttonTips.check_event(event)
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button_event.buttonReshow.check_event(event)
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if event.type == pygame.KEYDOWN:
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if(event.key == pygame.K_z):#Z键加快速度
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if map_game.ai_delay_time > 50:
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map_game.ai_delay_time = map_game.ai_delay_time - 50
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if(event.key == pygame.K_x):#X键减慢速度
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if map_game.ai_delay_time < 1000:
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map_game.ai_delay_time = map_game.ai_delay_time + 50
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if tisTime - lstTime > delaytime:
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lstTime = int(time.time()*1000)
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cc = copy.deepcopy(map_game.board_stack)
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if ii < len(cc):
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map_game.board = copy.deepcopy(cc[ii])
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ii = ii + 1
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sound.slide_sound()
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else:
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map_game.board = copy.deepcopy(reshow_temp_buf)
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game_state = 0
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sound.stop_sound()
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sound.background_sound()
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#独创AI算法(人工智障2.0)
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#贪心算法：
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#从四个方向遍历 并获取移动后的格局值 四个方向哪个方向的格局值最大就选哪一个
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def lanmeng():
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dir_num = [0,0,0,0]
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TestAIBoard = AI_map.AIMap(map_game.board)
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for direction in range(0,4):#四个方向都遍历一遍
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TestAIBoard2 = AI_map.AIMap(TestAIBoard.map)
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if TestAIBoard2.ai_go(direction) == False:#走不了就滚蛋吧
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dir_num[direction] = -999999
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else:
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dir_num[direction] = sum(TestAIBoard2.ai_evaluation())#将分析的结果加起来
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if max(dir_num) == -999999:
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return -1
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else:
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return dir_num.index(max(dir_num)) #选取得分最高的一个
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#独创AI算法(人工智障3.0)
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#minimax算法
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# 定义搜索结果类，用于方便处理返回值
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class searchResult:
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def __init__(self, move=-1, score=0, positions=0, cutoffs=0) -> None:
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self.move = move
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self.positions = positions
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self.cutoffs = cutoffs
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self.score = score
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def search(thisBoard: AI_map.AIMap, depth, alpha, beta, positions, cutoffs, playerTurn: bool):
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bestScore = 0
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bestMove = -1
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result = searchResult()
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if playerTurn == True: #玩家回合 倾向于让玩家获得最多的分数
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bestScore = alpha # 最高分为alpha
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for direction in range(4): # 四个方向分别进行遍历
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newBoard = AI_map.AIMap(thisBoard.map) # 新建一个棋盘防止影响到正式游戏
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changed = newBoard.ai_go(direction) # 相对应方向移动
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if changed == True: # 如果这个方向可以移动
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positions += 1 # positions自增
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if depth == 0: # 如果已经搜索到最底层了
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result.move = direction
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result.score = sum(newBoard.ai_evaluation()) # 返回当前局面的评价值
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else:
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result = search(newBoard, depth-1, bestScore, beta, positions, cutoffs, False) # 进行min轮，即让AI下出对局面最不利的一步
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if result.score > 9900:
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result.score -= 1
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positions = result.positions
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cutoffs = result.cutoffs # 将返回值进行处理
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if result.score > bestScore:
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bestScore = result.score
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bestMove = direction
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if bestScore > beta: # 如果最高值大于beta，则已经证明该走法优于前面的最优，则本深度下后面不用继续计算。
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cutoffs += 1
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return searchResult(bestMove, beta, positions, cutoffs)
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else: #AI回合 倾向于让玩家获得最少的分数
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bestScore = beta
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newBoard = AI_map.AIMap(thisBoard.map)
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score_2 = []
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score_4 = []
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worstSituation = []
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cells = []
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for i in range(4): #找到空格子
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for j in range(4):
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if newBoard.map[i][j] == 0:
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cells.append([i, j])
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for value in [2, 4]: #生成可能的所有情况，并进行评估
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for i in range(len(cells)):
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if newBoard.map[cells[i][0]][cells[i][1]] == 0:
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newBoard.map[cells[i][0]][cells[i][1]] = value
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if value == 2:
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score_2.append(-newBoard.smothness() + newBoard.islands())
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if value == 4:
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score_4.append(-newBoard.smothness() + newBoard.islands())
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newBoard.map[cells[i][0]][cells[i][1]] = 0
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maxScore = max(max(score_2), max(score_4)) #找到最差的情况
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for i in range(len(score_2)): # 最差的情况可能不止一种，所以遍历一遍防止遗漏
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if score_2[i] == maxScore:
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worstSituation.append([cells[i], 2])
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for i in range(len(score_4)):
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if score_4[i] == maxScore:
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worstSituation.append([cells[i], 4])
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for situation in worstSituation: # 遍历所有最差情况
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nnewBoard = AI_map.AIMap(thisBoard.map)
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positions += 1
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result = search(nnewBoard, depth, alpha, bestScore, positions, cutoffs, True) # 进一步搜索
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positions = result.positions
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cutoffs = result.cutoffs
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if result.score < bestScore:
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bestScore = result.score
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if bestScore < alpha: # 剪枝同理
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cutoffs += 1
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return searchResult(-1, alpha, positions, cutoffs)
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return searchResult(bestMove, bestScore, positions, cutoffs)
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def lanmeng2():
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depth = 3
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nAIMap = AI_map.AIMap(map_game.board)
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newBest = search(nAIMap, depth, -1000000, 1000000, 0, 0, True)
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return newBest.move
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#以下为回调函数
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#
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#
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#
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#
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#
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#
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#
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#
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#AI按键回调函数
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def ai_button_callback():
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sound.stop_sound()
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global game_state
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if game_state == 0:
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game_state = 1
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sound.ai_background_sound()
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else:
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game_state = 0
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sound.background_sound()
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#提示模式按键回调函数
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def tips_button_event():
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tips_direction = ai_find_direction()
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if tips_direction == 0:
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win32api.MessageBox(0,"下一步应该：往左","提示",win32con.MB_OK)
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elif tips_direction == 1:
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win32api.MessageBox(0,"下一步应该：往右","提示",win32con.MB_OK)
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elif tips_direction == 2:
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win32api.MessageBox(0,"下一步应该：往上","提示",win32con.MB_OK)
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elif tips_direction == 3:
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win32api.MessageBox(0,"下一步应该：往下","提示",win32con.MB_OK)
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else:
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win32api.MessageBox(0,"走不了了","提示",win32con.MB_OK)
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#回放功能回调函数
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def reshow_callback():
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sound.stop_sound()
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global game_state
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global ii
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global reshow_temp_buf
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if game_state != 2:
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sound.reshow_sound()
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game_state = 2 #不管什么模式进去就是回放模式
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ii = 1
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reshow_temp_buf = copy.deepcopy(map_game.board) #缓存下来
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