mirror of
https://github.com/ZhangXinNan/DL-with-Python-and-PyTorch2.git
synced 2025-10-24 01:14:28 +08:00
317 lines
124 KiB
Plaintext
317 lines
124 KiB
Plaintext
{
|
||
"cells": [
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 18.3 使用PyTorch实现Q-Learning\n",
|
||
"\t以下为实现Q-Learning的主要代码。\n",
|
||
"### 18.3.1 定义Q-Learing主函数\n",
|
||
"\t本节详细代码号为pytorch-18-01。"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"import time\n",
|
||
"import numpy as np\n",
|
||
"import tkinter as tk\n",
|
||
"from PIL import ImageTk, Image\n",
|
||
"\n",
|
||
"np.random.seed(1)\n",
|
||
"PhotoImage = ImageTk.PhotoImage\n",
|
||
"UNIT = 100\n",
|
||
"HEIGHT = 5\n",
|
||
"WIDTH = 5\n",
|
||
"\n",
|
||
"\n",
|
||
"class Env(tk.Tk):\n",
|
||
" def __init__(self):\n",
|
||
" super(Env, self).__init__()\n",
|
||
" self.action_space = ['u', 'd', 'l', 'r']\n",
|
||
" self.n_actions = len(self.action_space)\n",
|
||
" self.title('Q Learning')\n",
|
||
" self.geometry('{0}x{1}'.format(HEIGHT * UNIT, HEIGHT * UNIT))\n",
|
||
" self.shapes = self.load_images()\n",
|
||
" self.canvas = self._build_canvas()\n",
|
||
" self.texts = []\n",
|
||
"\n",
|
||
" def _build_canvas(self):\n",
|
||
" canvas = tk.Canvas(self, bg='white',\n",
|
||
" height=HEIGHT * UNIT,\n",
|
||
" width=WIDTH * UNIT)\n",
|
||
" # create grids\n",
|
||
" for c in range(0, WIDTH * UNIT, UNIT): # 0~400 by 100\n",
|
||
" x0, y0, x1, y1 = c, 0, c, HEIGHT * UNIT\n",
|
||
" canvas.create_line(x0, y0, x1, y1)\n",
|
||
" for r in range(0, HEIGHT * UNIT, UNIT): # 0~400 by 100\n",
|
||
" x0, y0, x1, y1 = 0, r, HEIGHT * UNIT, r\n",
|
||
" canvas.create_line(x0, y0, x1, y1)\n",
|
||
"\n",
|
||
" # 把图标加载到环境中\n",
|
||
" self.rectangle = canvas.create_image(50, 50, image=self.shapes[0])\n",
|
||
" self.tree1 = canvas.create_image(250, 150, image=self.shapes[1])\n",
|
||
" self.tree2 = canvas.create_image(150, 250, image=self.shapes[1])\n",
|
||
" self.star = canvas.create_image(250, 250, image=self.shapes[2])\n",
|
||
"\n",
|
||
" # 对环境进行包装\n",
|
||
" canvas.pack()\n",
|
||
"\n",
|
||
" return canvas\n",
|
||
"\n",
|
||
" def load_images(self):\n",
|
||
" rectangle = PhotoImage(\n",
|
||
" Image.open(\"img/bob.png\").resize((65, 65)))\n",
|
||
" tree = PhotoImage(\n",
|
||
" Image.open(\"img/tree.png\").resize((65, 65)))\n",
|
||
" star = PhotoImage(\n",
|
||
" Image.open(\"img/star.jpg\").resize((65, 65)))\n",
|
||
"\n",
|
||
" return rectangle, tree, star\n",
|
||
"\n",
|
||
" def text_value(self, row, col, contents, action, font='Helvetica', size=10,\n",
|
||
" style='normal', anchor=\"nw\"):\n",
|
||
" if action == 0:\n",
|
||
" origin_x, origin_y = 7, 42\n",
|
||
" elif action == 1:\n",
|
||
" origin_x, origin_y = 85, 42\n",
|
||
" elif action == 2:\n",
|
||
" origin_x, origin_y = 42, 5\n",
|
||
" else:\n",
|
||
" origin_x, origin_y = 42, 77\n",
|
||
"\n",
|
||
" x, y = origin_y + (UNIT * col), origin_x + (UNIT * row)\n",
|
||
" font = (font, str(size), style)\n",
|
||
" text = self.canvas.create_text(x, y, fill=\"black\", text=contents,\n",
|
||
" font=font, anchor=anchor)\n",
|
||
" return self.texts.append(text)\n",
|
||
"\n",
|
||
" def print_value_all(self, q_table):\n",
|
||
" for i in self.texts:\n",
|
||
" self.canvas.delete(i)\n",
|
||
" self.texts.clear()\n",
|
||
" for i in range(HEIGHT):\n",
|
||
" for j in range(WIDTH):\n",
|
||
" for action in range(0, 4):\n",
|
||
" state = [i, j]\n",
|
||
" if str(state) in q_table.keys():\n",
|
||
" temp = q_table[str(state)][action]\n",
|
||
" self.text_value(j, i, round(temp, 2), action)\n",
|
||
"\n",
|
||
" def coords_to_state(self, coords):\n",
|
||
" x = int((coords[0] - 50) / 100)\n",
|
||
" y = int((coords[1] - 50) / 100)\n",
|
||
" return [x, y]\n",
|
||
"\n",
|
||
" def state_to_coords(self, state):\n",
|
||
" x = int(state[0] * 100 + 50)\n",
|
||
" y = int(state[1] * 100 + 50)\n",
|
||
" return [x, y]\n",
|
||
"\n",
|
||
" def reset(self):\n",
|
||
" self.update()\n",
|
||
" time.sleep(0.5)\n",
|
||
" x, y = self.canvas.coords(self.rectangle)\n",
|
||
" self.canvas.move(self.rectangle, UNIT / 2 - x, UNIT / 2 - y)\n",
|
||
" self.render()\n",
|
||
" # return observation\n",
|
||
" return self.coords_to_state(self.canvas.coords(self.rectangle))\n",
|
||
"\n",
|
||
" def step(self, action):\n",
|
||
" state = self.canvas.coords(self.rectangle)\n",
|
||
" base_action = np.array([0, 0])\n",
|
||
" self.render()\n",
|
||
"\n",
|
||
" if action == 0: # up\n",
|
||
" if state[1] > UNIT:\n",
|
||
" base_action[1] -= UNIT\n",
|
||
" elif action == 1: # down\n",
|
||
" if state[1] < (HEIGHT - 1) * UNIT:\n",
|
||
" base_action[1] += UNIT\n",
|
||
" elif action == 2: # left\n",
|
||
" if state[0] > UNIT:\n",
|
||
" base_action[0] -= UNIT\n",
|
||
" elif action == 3: # right\n",
|
||
" if state[0] < (WIDTH - 1) * UNIT:\n",
|
||
" base_action[0] += UNIT\n",
|
||
"\n",
|
||
" # 移动\n",
|
||
" self.canvas.move(self.rectangle, base_action[0], base_action[1])\n",
|
||
" self.canvas.tag_raise(self.rectangle)\n",
|
||
" next_state = self.canvas.coords(self.rectangle)\n",
|
||
" # 判断得分条件\n",
|
||
" if next_state == self.canvas.coords(self.star):\n",
|
||
" reward = 100\n",
|
||
" done = True\n",
|
||
" elif next_state in [self.canvas.coords(self.tree1),\n",
|
||
" self.canvas.coords(self.tree2)]:\n",
|
||
" reward = -100\n",
|
||
" done = True\n",
|
||
" else:\n",
|
||
" reward = 0\n",
|
||
" done = False\n",
|
||
"\n",
|
||
" next_state = self.coords_to_state(next_state)\n",
|
||
" return next_state, reward, done\n",
|
||
"\n",
|
||
" # 渲染环境\n",
|
||
" def render(self):\n",
|
||
" time.sleep(0.03)\n",
|
||
" self.update()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 18.3.2执行Q-Learing\n",
|
||
"\t实例化环境,开始运行。"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"import random\n",
|
||
"from collections import defaultdict\n",
|
||
"\n",
|
||
"\n",
|
||
"class QLearningAgent:\n",
|
||
" def __init__(self, actions):\n",
|
||
" # 四种动作分别用序列表示:[0, 1, 2, 3]\n",
|
||
" self.actions = actions\n",
|
||
" self.learning_rate = 0.01\n",
|
||
" self.discount_factor = 0.9\n",
|
||
" #epsilon贪婪策略取值\n",
|
||
" self.epsilon = 0.1\n",
|
||
" self.q_table = defaultdict(lambda: [0.0, 0.0, 0.0, 0.0])\n",
|
||
"\n",
|
||
" # 采样 <s, a, r, s'>\n",
|
||
" def learn(self, state, action, reward, next_state):\n",
|
||
" current_q = self.q_table[state][action]\n",
|
||
" # 更新Q表\n",
|
||
" new_q = reward + self.discount_factor * max(self.q_table[next_state])\n",
|
||
" self.q_table[state][action] += self.learning_rate * (new_q - current_q)\n",
|
||
"\n",
|
||
" # 从Q-table中选取动作\n",
|
||
" def get_action(self, state):\n",
|
||
" if np.random.rand() < self.epsilon:\n",
|
||
" # 贪婪策略随机探索动作\n",
|
||
" action = np.random.choice(self.actions)\n",
|
||
" else:\n",
|
||
" # 从q表中选择\n",
|
||
" state_action = self.q_table[state]\n",
|
||
" action = self.arg_max(state_action)\n",
|
||
" return action\n",
|
||
"\n",
|
||
" @staticmethod\n",
|
||
" def arg_max(state_action):\n",
|
||
" max_index_list = []\n",
|
||
" max_value = state_action[0]\n",
|
||
" for index, value in enumerate(state_action):\n",
|
||
" if value > max_value:\n",
|
||
" max_index_list.clear()\n",
|
||
" max_value = value\n",
|
||
" max_index_list.append(index)\n",
|
||
" elif value == max_value:\n",
|
||
" max_index_list.append(index)\n",
|
||
" return random.choice(max_index_list)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"运行程序(如果是在远程服务器上运行,需要借助xshell客户端,即需要先用xshell连接服务器。 \n",
|
||
"如果在windows环境,不需要xshell)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"ename": "TclError",
|
||
"evalue": "invalid command name \".!canvas\"",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
|
||
"\u001b[1;31mTclError\u001b[0m Traceback (most recent call last)",
|
||
"\u001b[1;32m<ipython-input-3-1423cbadc276>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;31m#共进行200次游戏\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mepisode\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m200\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[0mstate\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0menv\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreset\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 6\u001b[0m \u001b[1;32mwhile\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[0menv\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrender\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||
"\u001b[1;32m<ipython-input-1-aa377bdeb320>\u001b[0m in \u001b[0;36mreset\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 101\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrender\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 102\u001b[0m \u001b[1;31m# return observation\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 103\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcoords_to_state\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcoords\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrectangle\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 104\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 105\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mstep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maction\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||
"\u001b[1;32m~\\Anaconda3\\lib\\tkinter\\__init__.py\u001b[0m in \u001b[0;36mcoords\u001b[1;34m(self, *args)\u001b[0m\n\u001b[0;32m 2467\u001b[0m return [self.tk.getdouble(x) for x in\n\u001b[0;32m 2468\u001b[0m self.tk.splitlist(\n\u001b[1;32m-> 2469\u001b[1;33m self.tk.call((self._w, 'coords') + args))]\n\u001b[0m\u001b[0;32m 2470\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_create\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mitemType\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;31m# Args: (val, val, ..., cnf={})\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2471\u001b[0m \u001b[1;34m\"\"\"Internal function.\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
||
"\u001b[1;31mTclError\u001b[0m: invalid command name \".!canvas\""
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"env = Env()\n",
|
||
"agent = QLearningAgent(actions=list(range(env.n_actions)))\n",
|
||
"#共进行200次游戏\n",
|
||
"for episode in range(200):\n",
|
||
" state = env.reset()\n",
|
||
" while True:\n",
|
||
" env.render()\n",
|
||
" # agent产生动作\n",
|
||
" action = agent.get_action(str(state))\n",
|
||
" next_state, reward, done = env.step(action)\n",
|
||
" # 更新Q表\n",
|
||
" agent.learn(str(state), action, reward, str(next_state))\n",
|
||
" state = next_state\n",
|
||
" env.print_value_all(agent.q_table)\n",
|
||
" # 当到达终点就终止游戏开始新一轮训练\n",
|
||
" if done:\n",
|
||
" break"
|
||
]
|
||
},
|
||
{
|
||
"attachments": {
|
||
"image.png": {
|
||
"image/png": "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"
|
||
}
|
||
},
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"运行结果示意图\n",
|
||
""
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.7.4"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|