日韩av黄I国产麻豆传媒I国产91av视频在线观看I日韩一区二区三区在线看I美女国产在线I麻豆视频国产在线观看I成人黄色短片

歡迎訪問(wèn) 生活随笔!

生活随笔

當(dāng)前位置: 首頁(yè) >

RL之Q Learning:利用强化学习之Q Learning实现走迷宫—训练智能体走到迷宫(复杂迷宫)的宝藏位置

發(fā)布時(shí)間:2025/3/21 36 豆豆
生活随笔 收集整理的這篇文章主要介紹了 RL之Q Learning:利用强化学习之Q Learning实现走迷宫—训练智能体走到迷宫(复杂迷宫)的宝藏位置 小編覺(jué)得挺不錯(cuò)的,現(xiàn)在分享給大家,幫大家做個(gè)參考.

RL之Q Learning:利用強(qiáng)化學(xué)習(xí)之Q Learning實(shí)現(xiàn)走迷宮—訓(xùn)練智能體走到迷宮(復(fù)雜迷宮)的寶藏位置

?

?

目錄

輸出結(jié)果

設(shè)計(jì)思路

實(shí)現(xiàn)代碼

測(cè)試記錄全過(guò)程


?

?

?

輸出結(jié)果

?

設(shè)計(jì)思路

?

?

?

實(shí)現(xiàn)代碼

from __future__ import print_function import numpy as np import time from env import Env from reprint import outputEPSILON = 0.1 ALPHA = 0.1 GAMMA = 0.9 MAX_STEP = 30np.random.seed(0)def epsilon_greedy(Q, state):if (np.random.uniform() > 1 - EPSILON) or ((Q[state, :] == 0).all()):action = np.random.randint(0, 4) # 0~3else:action = Q[state, :].argmax()return actione = Env() Q = np.zeros((e.state_num, 4))with output(output_type="list", initial_len=len(e.map), interval=0) as output_list:for i in range(100):e = Env()while (e.is_end is False) and (e.step < MAX_STEP):action = epsilon_greedy(Q, e.present_state)state = e.present_statereward = e.interact(action)new_state = e.present_stateQ[state, action] = (1 - ALPHA) * Q[state, action] + \ALPHA * (reward + GAMMA * Q[new_state, :].max())e.print_map_with_reprint(output_list)time.sleep(0.1)for line_num in range(len(e.map)):if line_num == 0:output_list[0] = 'Episode:{} Total Step:{}, Total Reward:{}'.format(i, e.step, e.total_reward)else:output_list[line_num] = ''time.sleep(2)

?

?

?

測(cè)試記錄全過(guò)程

開(kāi)始 ......... ......... . x . ......... . x . .A x o . ......... . x . .A x o . . . ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . x o . . . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . .A . ......... ......... . x . . x o . .A . ......... ......... . x . . x o . .A . ......... ......... . x . . x o . .A . ......... ......... . x . . x o . .A . ......... ......... . x . . x o . .A . ......... ......... . x . . x o . .A . ......... ......... . x . . x o . .A . ......... ......... . x . . x o . .A . ......... ......... . x . .A x o . .A . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . . x o . . . ......... ......... . x . . x o . .A . ......... ......... . x . . x o . .A . ......... ......... . x . . x o . .A . ......... ......... . x . . x o . .A . ......... ......... . x . .A x o . .A . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . .A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . x o . . . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x A . . A . ......... ......... . x . . x A . . . ......... ......... . x . . x A . . . ......... Episode:0 Total Step:17, Total Reward:100 . x . . x A . . . ......... Episode:0 Total Step:17, Total Reward:100 . x A . . . ......... Episode:0 Total Step:17, Total Reward:100 . . ......... Episode:0 Total Step:17, Total Reward:100 ......... Episode:0 Total Step:17, Total Reward:100 ......... ......... . x . ......... . x . .A x o . ......... . x . .A x o . . . ......... . x . .A x o . . . ......... ……......... . A . . x o . . . ......... Episode:2 Total Step:30, Total Reward:-5 . A . . x o . . . ......... Episode:2 Total Step:30, Total Reward:-5 . x o . . . ......... Episode:2 Total Step:30, Total Reward:-5 . . ......... Episode:2 Total Step:30, Total Reward:-5 ......... Episode:2 Total Step:30, Total Reward:-5 [F……......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . xAo . . A . ......... ......... . x . . xAo . . . ......... ......... . x . . xAo . . . ......... ......... . x . . xAo . . . ......... ......... . x . . xAo . . . ......... ......... . x . . x A . . . ......... ......... . x . . x A . . . ......... ......... . x . . x A . . . ......... Episode:98 Total Step:8, Total Reward:100 . x . . x A . . . ......... Episode:98 Total Step:8, Total Reward:100 . x A . . . ......... Episode:98 Total Step:8, Total Reward:100 . . ......... Episode:98 Total Step:8, Total Reward:100 ......... Episode:98 Total Step:8, Total Reward:100 ......... ......... . Ax . ......... . Ax . . x o . ......... . Ax . . x o . . . ......... . Ax . . x o . . . ......... ......... . Ax . . x o . . . ......... ......... . Ax . . x o . . . ......... ......... . Ax . . x o . . . ......... ......... . Ax . . x o . . . ......... ......... . Ax . . x o . . . ......... ......... . Ax . . x o . . . ......... ......... . x . . x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . A x o . . . ......... ......... . x . . x o . . . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . Ax o . . A . ......... ......... . x . . Ax o . . . ......... ......... . x . . Ax o . . . ......... ......... . x . . Ax o . . . ......... ......... . x . . Ax o . . . ......... ......... . x . . x o . . . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . x o . . A . ......... ......... . x . . xAo . . A . ......... ......... . x . . xAo . . . ......... ......... . x . . xAo . . . ......... ......... . x . . xAo . . . ......... ......... . x . . xAo . . . ......... ......... . x . . x A . . . ......... ......... . x . . x A . . . ......... ......... . x . . x A . . . ......... Episode:99 Total Step:11, Total Reward:100 . x . . x A . . . ......... Episode:99 Total Step:11, Total Reward:100 . x A . . . ......... Episode:99 Total Step:11, Total Reward:100 . . ......... Episode:99 Total Step:11, Total Reward:100 ......... Episode:99 Total Step:11, Total Reward:100 Episode:99 Total Step:11, Total Reward:100

?

?

?

?

總結(jié)

以上是生活随笔為你收集整理的RL之Q Learning:利用强化学习之Q Learning实现走迷宫—训练智能体走到迷宫(复杂迷宫)的宝藏位置的全部?jī)?nèi)容,希望文章能夠幫你解決所遇到的問(wèn)題。

如果覺(jué)得生活随笔網(wǎng)站內(nèi)容還不錯(cuò),歡迎將生活随笔推薦給好友。