Monte Carlon(Simple map).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d433738e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import gym\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c452433f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluate_policy(env, agent):\n",
    "    s_k, info = env.reset(seed=cfg_params[\"random_seed\"])\n",
    "    terminated = False\n",
    "    sum_reward = 0\n",
    "    for _ in range(cfg_params[\"max_episode_steps\"]):\n",
    "        a_k = agent.optimal_action(s_k)\n",
    "        s_k1, r_k, terminated, _ , info = env.step(a_k)\n",
    "#         print(f\"s_k: {s_k}, a_k: {a_k}, s_k1: {s_k1}, r_k: {r_k}, terminated: {terminated}\")\n",
    "        sum_reward += r_k\n",
    "        s_k = s_k1\n",
    "        if terminated:\n",
    "            break\n",
    "    return sum_reward\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6faa1c70",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Agent():\n",
    "    def __init__(self, action_dim: int, state_dim: int, alpha=0.01, gamma=0.9, epsilon=0.1):\n",
    "        self.action_dim = action_dim\n",
    "        self.state_dim = state_dim\n",
    "        self.alpha = alpha\n",
    "        self.gamma = gamma\n",
    "        self.epsilon = epsilon\n",
    "        self.Q = np.zeros((state_dim, action_dim))  # 查表法 action value: Q(s, a)\n",
    "        self.Returns = np.zeros((state_dim, action_dim))\n",
    "        self.Counts = np.zeros((state_dim, action_dim))\n",
    "    \n",
    "    def select_action(self, s_k: int) -> int:\n",
    "        '''use e-greedy policy'''\n",
    "        self.optimal_action\n",
    "        if np.random.uniform(0, 1) > self.epsilon:\n",
    "            a_k = self.optimal_action(s_k)\n",
    "        else:\n",
    "            a_k = np.random.choice(self.action_dim)\n",
    "        return a_k\n",
    "    \n",
    "    def optimal_action(self, s_k: int) -> int:\n",
    "        Q_sk = self.Q[s_k, :]\n",
    "        optimal_action_list = np.where(Q_sk == np.max(Q_sk))[0]\n",
    "        return np.random.choice(optimal_action_list)\n",
    "    \n",
    "    def other_action(self, s_k: int) -> int:\n",
    "        Q_sk = self.Q[s_k, :]\n",
    "        other_action_list = np.where(Q_sk != np.max(Q_sk))[0]\n",
    "        return np.random.choice(other_action_list)\n",
    "    \n",
    "    def train(self, s_k, a_k, r_k, s_k1):\n",
    "        # QLearning Algorithm\n",
    "        target_Q = r_k + self.gamma * np.max(self.Q[s_k1, :])\n",
    "        Q_sa = self.Q[s_k, a_k]\n",
    "        self.Q[s_k, a_k] += self.alpha* (target_Q - Q_sa)\n",
    "    \n",
    "    def MonteCarlo_train(self, data_queue: list):\n",
    "        # policy evaluation\n",
    "        data_array = np.array(data_queue)\n",
    "        sar_set = set([(x[0], x[1]) for x in data_array])\n",
    "        for (sk, ak) in sar_set:        \n",
    "            first_visited_idx = [i for i, x in enumerate(data_array) if x[0] == sk and x[1] == ak]\n",
    "            g = sum([(self.gamma**i)*rk for i, rk in enumerate(data_array[:, 2][first_visited_idx[0]:])])\n",
    "            self.Returns[int(sk), int(ak)] += g\n",
    "            self.Counts[int(sk), int(ak)] += 1\n",
    "            \n",
    "            self.Q[int(sk), int(ak)] = self.Returns[int(sk), int(ak)] / self.Counts[int(sk), int(ak)]\n",
    "        \n",
    "        "
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "fc8e5e22",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "12e66c1a",
   "metadata": {},
   "source": [
    "![image-2.png](attachment:image-2.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9b35eb96",
   "metadata": {},
   "outputs": [],
   "source": [
    "# parameter\n",
    "cfg_params = {\n",
    "    \"env_name\" : \"FrozenLake-v1\",\n",
    "    \"random_seed\": 0,\n",
    "    \"max_train_steps\": 1000,\n",
    "    \"max_episode_steps\": 500,\n",
    "}\n",
    "\n",
    "env = gym.make(cfg_params[\"env_name\"], desc=None, map_name=\"4x4\", is_slippery=True) #  gym.make(\"CliffWalking-v0\", render_mode=\"human\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e5ceadb",
   "metadata": {},
   "source": [
    "Environment Model\n",
    "$p(r_k\\vert s_k, a_k)\\\\p(s_{k+1}\\vert s_k, a_k)$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ae9347bf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "current step: 0/1000, score: 0.0\n",
      "current step: 1/1000, score: 0.0\n",
      "current step: 2/1000, score: 0.0\n",
      "current step: 3/1000, score: 0.0\n",
      "current step: 4/1000, score: 0.0\n",
      "current step: 5/1000, score: 0.0\n",
      "current step: 6/1000, score: 0.0\n",
      "current step: 7/1000, score: 0.0\n",
      "current step: 8/1000, score: 0.0\n",
      "current step: 9/1000, score: 0.0\n",
      "current step: 10/1000, score: 0.0\n",
      "current step: 11/1000, score: 0.0\n",
      "current step: 12/1000, score: 0.0\n",
      "current step: 13/1000, score: 0.0\n",
      "current step: 14/1000, score: 0.0\n",
      "current step: 15/1000, score: 0.0\n",
      "current step: 16/1000, score: 0.0\n",
      "current step: 17/1000, score: 0.0\n",
      "current step: 18/1000, score: 0.0\n",
      "current step: 19/1000, score: 0.0\n",
      "current step: 20/1000, score: 0.0\n",
      "current step: 21/1000, score: 0.0\n",
      "current step: 22/1000, score: 0.0\n",
      "current step: 23/1000, score: 0.0\n",
      "current step: 24/1000, score: 0.0\n",
      "current step: 25/1000, score: 0.0\n",
      "current step: 26/1000, score: 0.0\n",
      "current step: 27/1000, score: 0.0\n",
      "current step: 28/1000, score: 0.0\n",
      "current step: 29/1000, score: 0.0\n",
      "current step: 30/1000, score: 0.0\n",
      "current step: 31/1000, score: 0.0\n",
      "current step: 32/1000, score: 0.0\n",
      "current step: 33/1000, score: 0.0\n",
      "current step: 34/1000, score: 0.0\n",
      "current step: 35/1000, score: 0.0\n",
      "current step: 36/1000, score: 0.0\n",
      "current step: 37/1000, score: 0.0\n",
      "current step: 38/1000, score: 0.0\n",
      "current step: 39/1000, score: 0.0\n",
      "current step: 40/1000, score: 0.0\n",
      "current step: 41/1000, score: 0.0\n",
      "current step: 42/1000, score: 0.0\n",
      "current step: 43/1000, score: 0.0\n",
      "current step: 44/1000, score: 0.0\n",
      "current step: 45/1000, score: 0.0\n",
      "current step: 46/1000, score: 0.0\n",
      "current step: 47/1000, score: 1.0\n",
      "current step: 48/1000, score: 0.0\n",
      "current step: 49/1000, score: 0.0\n",
      "current step: 50/1000, score: 1.0\n",
      "current step: 51/1000, score: 1.0\n",
      "current step: 52/1000, score: 1.0\n",
      "current step: 53/1000, score: 1.0\n",
      "current step: 54/1000, score: 0.0\n",
      "current step: 55/1000, score: 1.0\n",
      "current step: 56/1000, score: 1.0\n",
      "current step: 57/1000, score: 1.0\n",
      "current step: 58/1000, score: 1.0\n",
      "current step: 59/1000, score: 1.0\n",
      "current step: 60/1000, score: 1.0\n",
      "current step: 61/1000, score: 0.0\n",
      "current step: 62/1000, score: 1.0\n",
      "current step: 63/1000, score: 1.0\n",
      "current step: 64/1000, score: 0.0\n",
      "current step: 65/1000, score: 1.0\n",
      "current step: 66/1000, score: 1.0\n",
      "current step: 67/1000, score: 1.0\n",
      "current step: 68/1000, score: 1.0\n",
      "current step: 69/1000, score: 1.0\n",
      "current step: 70/1000, score: 0.0\n",
      "current step: 71/1000, score: 1.0\n",
      "current step: 72/1000, score: 1.0\n",
      "current step: 73/1000, score: 1.0\n",
      "current step: 74/1000, score: 1.0\n",
      "current step: 75/1000, score: 0.0\n",
      "current step: 76/1000, score: 0.0\n",
      "current step: 77/1000, score: 1.0\n",
      "current step: 78/1000, score: 0.0\n",
      "current step: 79/1000, score: 1.0\n",
      "current step: 80/1000, score: 1.0\n",
      "current step: 81/1000, score: 1.0\n",
      "current step: 82/1000, score: 1.0\n",
      "current step: 83/1000, score: 1.0\n",
      "current step: 84/1000, score: 1.0\n",
      "current step: 85/1000, score: 1.0\n",
      "current step: 86/1000, score: 1.0\n",
      "current step: 87/1000, score: 1.0\n",
      "current step: 88/1000, score: 1.0\n",
      "current step: 89/1000, score: 1.0\n",
      "current step: 90/1000, score: 1.0\n",
      "current step: 91/1000, score: 1.0\n",
      "current step: 92/1000, score: 1.0\n",
      "current step: 93/1000, score: 1.0\n",
      "current step: 94/1000, score: 1.0\n",
      "current step: 95/1000, score: 1.0\n",
      "current step: 96/1000, score: 1.0\n",
      "current step: 97/1000, score: 1.0\n",
      "current step: 98/1000, score: 1.0\n",
      "current step: 99/1000, score: 1.0\n",
      "current step: 100/1000, score: 1.0\n",
      "current step: 101/1000, score: 1.0\n",
      "current step: 102/1000, score: 1.0\n",
      "current step: 103/1000, score: 1.0\n",
      "current step: 104/1000, score: 1.0\n",
      "current step: 105/1000, score: 1.0\n",
      "current step: 106/1000, score: 1.0\n",
      "current step: 107/1000, score: 1.0\n",
      "current step: 108/1000, score: 1.0\n",
      "current step: 109/1000, score: 1.0\n",
      "current step: 110/1000, score: 1.0\n",
      "current step: 111/1000, score: 1.0\n",
      "current step: 112/1000, score: 1.0\n",
      "current step: 113/1000, score: 1.0\n",
      "current step: 114/1000, score: 1.0\n",
      "current step: 115/1000, score: 1.0\n",
      "current step: 116/1000, score: 1.0\n",
      "current step: 117/1000, score: 1.0\n",
      "current step: 118/1000, score: 1.0\n",
      "current step: 119/1000, score: 1.0\n",
      "current step: 120/1000, score: 1.0\n",
      "current step: 121/1000, score: 1.0\n",
      "current step: 122/1000, score: 1.0\n",
      "current step: 123/1000, score: 1.0\n",
      "current step: 124/1000, score: 1.0\n",
      "current step: 125/1000, score: 1.0\n",
      "current step: 126/1000, score: 1.0\n",
      "current step: 127/1000, score: 1.0\n",
      "current step: 128/1000, score: 1.0\n",
      "current step: 129/1000, score: 1.0\n",
      "current step: 130/1000, score: 1.0\n",
      "current step: 131/1000, score: 1.0\n",
      "current step: 132/1000, score: 1.0\n",
      "current step: 133/1000, score: 1.0\n",
      "current step: 134/1000, score: 1.0\n",
      "current step: 135/1000, score: 1.0\n",
      "current step: 136/1000, score: 1.0\n",
      "current step: 137/1000, score: 1.0\n",
      "current step: 138/1000, score: 1.0\n",
      "current step: 139/1000, score: 1.0\n",
      "current step: 140/1000, score: 1.0\n",
      "current step: 141/1000, score: 1.0\n",
      "current step: 142/1000, score: 1.0\n",
      "current step: 143/1000, score: 1.0\n",
      "current step: 144/1000, score: 1.0\n",
      "current step: 145/1000, score: 1.0\n",
      "current step: 146/1000, score: 1.0\n",
      "current step: 147/1000, score: 1.0\n",
      "current step: 148/1000, score: 1.0\n",
      "current step: 149/1000, score: 1.0\n",
      "current step: 150/1000, score: 1.0\n",
      "current step: 151/1000, score: 1.0\n",
      "current step: 152/1000, score: 1.0\n",
      "current step: 153/1000, score: 1.0\n",
      "current step: 154/1000, score: 1.0\n",
      "current step: 155/1000, score: 1.0\n",
      "current step: 156/1000, score: 1.0\n",
      "current step: 157/1000, score: 1.0\n",
      "current step: 158/1000, score: 1.0\n",
      "current step: 159/1000, score: 1.0\n",
      "current step: 160/1000, score: 1.0\n",
      "current step: 161/1000, score: 1.0\n",
      "current step: 162/1000, score: 1.0\n",
      "current step: 163/1000, score: 1.0\n",
      "current step: 164/1000, score: 1.0\n",
      "current step: 165/1000, score: 1.0\n",
      "current step: 166/1000, score: 1.0\n",
      "current step: 167/1000, score: 1.0\n",
      "current step: 168/1000, score: 1.0\n",
      "current step: 169/1000, score: 1.0\n",
      "current step: 170/1000, score: 1.0\n",
      "current step: 171/1000, score: 1.0\n",
      "current step: 172/1000, score: 1.0\n",
      "current step: 173/1000, score: 1.0\n",
      "current step: 174/1000, score: 1.0\n",
      "current step: 175/1000, score: 1.0\n",
      "current step: 176/1000, score: 1.0\n",
      "current step: 177/1000, score: 1.0\n",
      "current step: 178/1000, score: 1.0\n",
      "current step: 179/1000, score: 1.0\n",
      "current step: 180/1000, score: 1.0\n",
      "current step: 181/1000, score: 1.0\n",
      "current step: 182/1000, score: 1.0\n",
      "current step: 183/1000, score: 1.0\n",
      "current step: 184/1000, score: 1.0\n",
      "current step: 185/1000, score: 1.0\n",
      "current step: 186/1000, score: 1.0\n",
      "current step: 187/1000, score: 1.0\n",
      "current step: 188/1000, score: 1.0\n",
      "current step: 189/1000, score: 1.0\n",
      "current step: 190/1000, score: 1.0\n",
      "current step: 191/1000, score: 1.0\n",
      "current step: 192/1000, score: 1.0\n",
      "current step: 193/1000, score: 1.0\n",
      "current step: 194/1000, score: 1.0\n",
      "current step: 195/1000, score: 1.0\n",
      "current step: 196/1000, score: 1.0\n",
      "current step: 197/1000, score: 1.0\n",
      "current step: 198/1000, score: 1.0\n",
      "current step: 199/1000, score: 1.0\n",
      "current step: 200/1000, score: 1.0\n",
      "current step: 201/1000, score: 1.0\n",
      "current step: 202/1000, score: 1.0\n",
      "current step: 203/1000, score: 1.0\n",
      "current step: 204/1000, score: 1.0\n",
      "current step: 205/1000, score: 1.0\n",
      "current step: 206/1000, score: 1.0\n",
      "current step: 207/1000, score: 1.0\n",
      "current step: 208/1000, score: 1.0\n",
      "current step: 209/1000, score: 1.0\n",
      "current step: 210/1000, score: 1.0\n",
      "current step: 211/1000, score: 1.0\n",
      "current step: 212/1000, score: 1.0\n",
      "current step: 213/1000, score: 1.0\n",
      "current step: 214/1000, score: 1.0\n",
      "current step: 215/1000, score: 1.0\n",
      "current step: 216/1000, score: 1.0\n",
      "current step: 217/1000, score: 1.0\n",
      "current step: 218/1000, score: 1.0\n",
      "current step: 219/1000, score: 1.0\n",
      "current step: 220/1000, score: 1.0\n",
      "current step: 221/1000, score: 1.0\n",
      "current step: 222/1000, score: 1.0\n",
      "current step: 223/1000, score: 1.0\n",
      "current step: 224/1000, score: 1.0\n",
      "current step: 225/1000, score: 1.0\n",
      "current step: 226/1000, score: 1.0\n",
      "current step: 227/1000, score: 1.0\n",
      "current step: 228/1000, score: 1.0\n",
      "current step: 229/1000, score: 1.0\n",
      "current step: 230/1000, score: 1.0\n",
      "current step: 231/1000, score: 1.0\n",
      "current step: 232/1000, score: 1.0\n",
      "current step: 233/1000, score: 1.0\n",
      "current step: 234/1000, score: 1.0\n",
      "current step: 235/1000, score: 1.0\n",
      "current step: 236/1000, score: 1.0\n",
      "current step: 237/1000, score: 1.0\n",
      "current step: 238/1000, score: 1.0\n",
      "current step: 239/1000, score: 1.0\n",
      "current step: 240/1000, score: 1.0\n",
      "current step: 241/1000, score: 1.0\n",
      "current step: 242/1000, score: 1.0\n",
      "current step: 243/1000, score: 1.0\n",
      "current step: 244/1000, score: 1.0\n",
      "current step: 245/1000, score: 1.0\n",
      "current step: 246/1000, score: 1.0\n",
      "current step: 247/1000, score: 1.0\n",
      "current step: 248/1000, score: 1.0\n",
      "current step: 249/1000, score: 1.0\n",
      "current step: 250/1000, score: 1.0\n",
      "current step: 251/1000, score: 1.0\n",
      "current step: 252/1000, score: 1.0\n",
      "current step: 253/1000, score: 1.0\n",
      "current step: 254/1000, score: 1.0\n",
      "current step: 255/1000, score: 1.0\n",
      "current step: 256/1000, score: 1.0\n",
      "current step: 257/1000, score: 1.0\n",
      "current step: 258/1000, score: 1.0\n",
      "current step: 259/1000, score: 1.0\n",
      "current step: 260/1000, score: 1.0\n",
      "current step: 261/1000, score: 1.0\n",
      "current step: 262/1000, score: 1.0\n",
      "current step: 263/1000, score: 1.0\n",
      "current step: 264/1000, score: 1.0\n",
      "current step: 265/1000, score: 1.0\n",
      "current step: 266/1000, score: 1.0\n",
      "current step: 267/1000, score: 1.0\n",
      "current step: 268/1000, score: 1.0\n",
      "current step: 269/1000, score: 1.0\n",
      "current step: 270/1000, score: 1.0\n",
      "current step: 271/1000, score: 1.0\n",
      "current step: 272/1000, score: 1.0\n",
      "current step: 273/1000, score: 1.0\n",
      "current step: 274/1000, score: 1.0\n",
      "current step: 275/1000, score: 1.0\n",
      "current step: 276/1000, score: 1.0\n",
      "current step: 277/1000, score: 1.0\n",
      "current step: 278/1000, score: 1.0\n",
      "current step: 279/1000, score: 1.0\n",
      "current step: 280/1000, score: 1.0\n",
      "current step: 281/1000, score: 1.0\n",
      "current step: 282/1000, score: 1.0\n",
      "current step: 283/1000, score: 1.0\n",
      "current step: 284/1000, score: 1.0\n",
      "current step: 285/1000, score: 1.0\n",
      "current step: 286/1000, score: 1.0\n",
      "current step: 287/1000, score: 1.0\n",
      "current step: 288/1000, score: 1.0\n",
      "current step: 289/1000, score: 1.0\n",
      "current step: 290/1000, score: 1.0\n",
      "current step: 291/1000, score: 1.0\n",
      "current step: 292/1000, score: 1.0\n",
      "current step: 293/1000, score: 1.0\n",
      "current step: 294/1000, score: 1.0\n",
      "current step: 295/1000, score: 1.0\n",
      "current step: 296/1000, score: 1.0\n",
      "current step: 297/1000, score: 1.0\n",
      "current step: 298/1000, score: 1.0\n",
      "current step: 299/1000, score: 1.0\n",
      "current step: 300/1000, score: 1.0\n",
      "current step: 301/1000, score: 1.0\n",
      "current step: 302/1000, score: 1.0\n",
      "current step: 303/1000, score: 1.0\n",
      "current step: 304/1000, score: 1.0\n",
      "current step: 305/1000, score: 1.0\n",
      "current step: 306/1000, score: 1.0\n",
      "current step: 307/1000, score: 1.0\n",
      "current step: 308/1000, score: 1.0\n",
      "current step: 309/1000, score: 1.0\n",
      "current step: 310/1000, score: 1.0\n",
      "current step: 311/1000, score: 1.0\n",
      "current step: 312/1000, score: 1.0\n",
      "current step: 313/1000, score: 1.0\n",
      "current step: 314/1000, score: 1.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "current step: 315/1000, score: 1.0\n",
      "current step: 316/1000, score: 1.0\n",
      "current step: 317/1000, score: 1.0\n",
      "current step: 318/1000, score: 1.0\n",
      "current step: 319/1000, score: 1.0\n",
      "current step: 320/1000, score: 1.0\n",
      "current step: 321/1000, score: 1.0\n",
      "current step: 322/1000, score: 1.0\n",
      "current step: 323/1000, score: 1.0\n",
      "current step: 324/1000, score: 1.0\n",
      "current step: 325/1000, score: 1.0\n",
      "current step: 326/1000, score: 1.0\n",
      "current step: 327/1000, score: 1.0\n",
      "current step: 328/1000, score: 1.0\n",
      "current step: 329/1000, score: 1.0\n",
      "current step: 330/1000, score: 1.0\n",
      "current step: 331/1000, score: 1.0\n",
      "current step: 332/1000, score: 1.0\n",
      "current step: 333/1000, score: 1.0\n",
      "current step: 334/1000, score: 1.0\n",
      "current step: 335/1000, score: 1.0\n",
      "current step: 336/1000, score: 1.0\n",
      "current step: 337/1000, score: 1.0\n",
      "current step: 338/1000, score: 1.0\n",
      "current step: 339/1000, score: 1.0\n",
      "current step: 340/1000, score: 1.0\n",
      "current step: 341/1000, score: 1.0\n",
      "current step: 342/1000, score: 1.0\n",
      "current step: 343/1000, score: 1.0\n",
      "current step: 344/1000, score: 1.0\n",
      "current step: 345/1000, score: 1.0\n",
      "current step: 346/1000, score: 1.0\n",
      "current step: 347/1000, score: 1.0\n",
      "current step: 348/1000, score: 1.0\n",
      "current step: 349/1000, score: 1.0\n",
      "current step: 350/1000, score: 1.0\n",
      "current step: 351/1000, score: 1.0\n",
      "current step: 352/1000, score: 1.0\n",
      "current step: 353/1000, score: 1.0\n",
      "current step: 354/1000, score: 1.0\n",
      "current step: 355/1000, score: 1.0\n",
      "current step: 356/1000, score: 1.0\n",
      "current step: 357/1000, score: 1.0\n",
      "current step: 358/1000, score: 1.0\n",
      "current step: 359/1000, score: 1.0\n",
      "current step: 360/1000, score: 1.0\n",
      "current step: 361/1000, score: 1.0\n",
      "current step: 362/1000, score: 1.0\n",
      "current step: 363/1000, score: 1.0\n",
      "current step: 364/1000, score: 1.0\n",
      "current step: 365/1000, score: 1.0\n",
      "current step: 366/1000, score: 1.0\n",
      "current step: 367/1000, score: 1.0\n",
      "current step: 368/1000, score: 1.0\n",
      "current step: 369/1000, score: 1.0\n",
      "current step: 370/1000, score: 1.0\n",
      "current step: 371/1000, score: 1.0\n",
      "current step: 372/1000, score: 1.0\n",
      "current step: 373/1000, score: 1.0\n",
      "current step: 374/1000, score: 1.0\n",
      "current step: 375/1000, score: 1.0\n",
      "current step: 376/1000, score: 1.0\n",
      "current step: 377/1000, score: 1.0\n",
      "current step: 378/1000, score: 1.0\n",
      "current step: 379/1000, score: 1.0\n",
      "current step: 380/1000, score: 1.0\n",
      "current step: 381/1000, score: 1.0\n",
      "current step: 382/1000, score: 1.0\n",
      "current step: 383/1000, score: 1.0\n",
      "current step: 384/1000, score: 1.0\n",
      "current step: 385/1000, score: 1.0\n",
      "current step: 386/1000, score: 1.0\n",
      "current step: 387/1000, score: 1.0\n",
      "current step: 388/1000, score: 1.0\n",
      "current step: 389/1000, score: 1.0\n",
      "current step: 390/1000, score: 1.0\n",
      "current step: 391/1000, score: 1.0\n",
      "current step: 392/1000, score: 1.0\n",
      "current step: 393/1000, score: 1.0\n",
      "current step: 394/1000, score: 1.0\n",
      "current step: 395/1000, score: 1.0\n",
      "current step: 396/1000, score: 1.0\n",
      "current step: 397/1000, score: 1.0\n",
      "current step: 398/1000, score: 1.0\n",
      "current step: 399/1000, score: 1.0\n",
      "current step: 400/1000, score: 1.0\n",
      "current step: 401/1000, score: 1.0\n",
      "current step: 402/1000, score: 1.0\n",
      "current step: 403/1000, score: 1.0\n",
      "current step: 404/1000, score: 1.0\n",
      "current step: 405/1000, score: 1.0\n",
      "current step: 406/1000, score: 1.0\n",
      "current step: 407/1000, score: 1.0\n",
      "current step: 408/1000, score: 1.0\n",
      "current step: 409/1000, score: 1.0\n",
      "current step: 410/1000, score: 1.0\n",
      "current step: 411/1000, score: 1.0\n",
      "current step: 412/1000, score: 1.0\n",
      "current step: 413/1000, score: 1.0\n",
      "current step: 414/1000, score: 1.0\n",
      "current step: 415/1000, score: 1.0\n",
      "current step: 416/1000, score: 1.0\n",
      "current step: 417/1000, score: 1.0\n",
      "current step: 418/1000, score: 1.0\n",
      "current step: 419/1000, score: 1.0\n",
      "current step: 420/1000, score: 1.0\n",
      "current step: 421/1000, score: 1.0\n",
      "current step: 422/1000, score: 1.0\n",
      "current step: 423/1000, score: 1.0\n",
      "current step: 424/1000, score: 1.0\n",
      "current step: 425/1000, score: 1.0\n",
      "current step: 426/1000, score: 1.0\n",
      "current step: 427/1000, score: 1.0\n",
      "current step: 428/1000, score: 1.0\n",
      "current step: 429/1000, score: 1.0\n",
      "current step: 430/1000, score: 1.0\n",
      "current step: 431/1000, score: 1.0\n",
      "current step: 432/1000, score: 1.0\n",
      "current step: 433/1000, score: 1.0\n",
      "current step: 434/1000, score: 1.0\n",
      "current step: 435/1000, score: 1.0\n",
      "current step: 436/1000, score: 1.0\n",
      "current step: 437/1000, score: 1.0\n",
      "current step: 438/1000, score: 1.0\n",
      "current step: 439/1000, score: 1.0\n",
      "current step: 440/1000, score: 1.0\n",
      "current step: 441/1000, score: 1.0\n",
      "current step: 442/1000, score: 1.0\n",
      "current step: 443/1000, score: 1.0\n",
      "current step: 444/1000, score: 1.0\n",
      "current step: 445/1000, score: 1.0\n",
      "current step: 446/1000, score: 1.0\n",
      "current step: 447/1000, score: 1.0\n",
      "current step: 448/1000, score: 1.0\n",
      "current step: 449/1000, score: 1.0\n",
      "current step: 450/1000, score: 1.0\n",
      "current step: 451/1000, score: 1.0\n",
      "current step: 452/1000, score: 1.0\n",
      "current step: 453/1000, score: 1.0\n",
      "current step: 454/1000, score: 1.0\n",
      "current step: 455/1000, score: 1.0\n",
      "current step: 456/1000, score: 1.0\n",
      "current step: 457/1000, score: 1.0\n",
      "current step: 458/1000, score: 1.0\n",
      "current step: 459/1000, score: 1.0\n",
      "current step: 460/1000, score: 1.0\n",
      "current step: 461/1000, score: 1.0\n",
      "current step: 462/1000, score: 1.0\n",
      "current step: 463/1000, score: 1.0\n",
      "current step: 464/1000, score: 1.0\n",
      "current step: 465/1000, score: 1.0\n",
      "current step: 466/1000, score: 1.0\n",
      "current step: 467/1000, score: 1.0\n",
      "current step: 468/1000, score: 1.0\n",
      "current step: 469/1000, score: 1.0\n",
      "current step: 470/1000, score: 1.0\n",
      "current step: 471/1000, score: 1.0\n",
      "current step: 472/1000, score: 1.0\n",
      "current step: 473/1000, score: 1.0\n",
      "current step: 474/1000, score: 1.0\n",
      "current step: 475/1000, score: 1.0\n",
      "current step: 476/1000, score: 1.0\n",
      "current step: 477/1000, score: 1.0\n",
      "current step: 478/1000, score: 1.0\n",
      "current step: 479/1000, score: 1.0\n",
      "current step: 480/1000, score: 1.0\n",
      "current step: 481/1000, score: 1.0\n",
      "current step: 482/1000, score: 1.0\n",
      "current step: 483/1000, score: 1.0\n",
      "current step: 484/1000, score: 1.0\n",
      "current step: 485/1000, score: 1.0\n",
      "current step: 486/1000, score: 1.0\n",
      "current step: 487/1000, score: 1.0\n",
      "current step: 488/1000, score: 1.0\n",
      "current step: 489/1000, score: 1.0\n",
      "current step: 490/1000, score: 1.0\n",
      "current step: 491/1000, score: 1.0\n",
      "current step: 492/1000, score: 1.0\n",
      "current step: 493/1000, score: 1.0\n",
      "current step: 494/1000, score: 1.0\n",
      "current step: 495/1000, score: 1.0\n",
      "current step: 496/1000, score: 1.0\n",
      "current step: 497/1000, score: 1.0\n",
      "current step: 498/1000, score: 1.0\n",
      "current step: 499/1000, score: 1.0\n",
      "current step: 500/1000, score: 1.0\n",
      "current step: 501/1000, score: 1.0\n",
      "current step: 502/1000, score: 1.0\n",
      "current step: 503/1000, score: 1.0\n",
      "current step: 504/1000, score: 1.0\n",
      "current step: 505/1000, score: 1.0\n",
      "current step: 506/1000, score: 1.0\n",
      "current step: 507/1000, score: 1.0\n",
      "current step: 508/1000, score: 1.0\n",
      "current step: 509/1000, score: 1.0\n",
      "current step: 510/1000, score: 1.0\n",
      "current step: 511/1000, score: 1.0\n",
      "current step: 512/1000, score: 1.0\n",
      "current step: 513/1000, score: 1.0\n",
      "current step: 514/1000, score: 1.0\n",
      "current step: 515/1000, score: 1.0\n",
      "current step: 516/1000, score: 1.0\n",
      "current step: 517/1000, score: 1.0\n",
      "current step: 518/1000, score: 1.0\n",
      "current step: 519/1000, score: 1.0\n",
      "current step: 520/1000, score: 1.0\n",
      "current step: 521/1000, score: 1.0\n",
      "current step: 522/1000, score: 1.0\n",
      "current step: 523/1000, score: 1.0\n",
      "current step: 524/1000, score: 1.0\n",
      "current step: 525/1000, score: 1.0\n",
      "current step: 526/1000, score: 1.0\n",
      "current step: 527/1000, score: 1.0\n",
      "current step: 528/1000, score: 1.0\n",
      "current step: 529/1000, score: 1.0\n",
      "current step: 530/1000, score: 1.0\n",
      "current step: 531/1000, score: 1.0\n",
      "current step: 532/1000, score: 1.0\n",
      "current step: 533/1000, score: 1.0\n",
      "current step: 534/1000, score: 1.0\n",
      "current step: 535/1000, score: 1.0\n",
      "current step: 536/1000, score: 1.0\n",
      "current step: 537/1000, score: 1.0\n",
      "current step: 538/1000, score: 1.0\n",
      "current step: 539/1000, score: 1.0\n",
      "current step: 540/1000, score: 1.0\n",
      "current step: 541/1000, score: 1.0\n",
      "current step: 542/1000, score: 1.0\n",
      "current step: 543/1000, score: 1.0\n",
      "current step: 544/1000, score: 1.0\n",
      "current step: 545/1000, score: 1.0\n",
      "current step: 546/1000, score: 1.0\n",
      "current step: 547/1000, score: 1.0\n",
      "current step: 548/1000, score: 1.0\n",
      "current step: 549/1000, score: 1.0\n",
      "current step: 550/1000, score: 1.0\n",
      "current step: 551/1000, score: 1.0\n",
      "current step: 552/1000, score: 1.0\n",
      "current step: 553/1000, score: 1.0\n",
      "current step: 554/1000, score: 1.0\n",
      "current step: 555/1000, score: 1.0\n",
      "current step: 556/1000, score: 1.0\n",
      "current step: 557/1000, score: 1.0\n",
      "current step: 558/1000, score: 1.0\n",
      "current step: 559/1000, score: 1.0\n",
      "current step: 560/1000, score: 1.0\n",
      "current step: 561/1000, score: 1.0\n",
      "current step: 562/1000, score: 1.0\n",
      "current step: 563/1000, score: 1.0\n",
      "current step: 564/1000, score: 1.0\n",
      "current step: 565/1000, score: 1.0\n",
      "current step: 566/1000, score: 1.0\n",
      "current step: 567/1000, score: 1.0\n",
      "current step: 568/1000, score: 1.0\n",
      "current step: 569/1000, score: 1.0\n",
      "current step: 570/1000, score: 1.0\n",
      "current step: 571/1000, score: 1.0\n",
      "current step: 572/1000, score: 1.0\n",
      "current step: 573/1000, score: 1.0\n",
      "current step: 574/1000, score: 1.0\n",
      "current step: 575/1000, score: 1.0\n",
      "current step: 576/1000, score: 1.0\n",
      "current step: 577/1000, score: 1.0\n",
      "current step: 578/1000, score: 1.0\n",
      "current step: 579/1000, score: 1.0\n",
      "current step: 580/1000, score: 1.0\n",
      "current step: 581/1000, score: 1.0\n",
      "current step: 582/1000, score: 1.0\n",
      "current step: 583/1000, score: 1.0\n",
      "current step: 584/1000, score: 1.0\n",
      "current step: 585/1000, score: 1.0\n",
      "current step: 586/1000, score: 1.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "current step: 587/1000, score: 1.0\n",
      "current step: 588/1000, score: 1.0\n",
      "current step: 589/1000, score: 1.0\n",
      "current step: 590/1000, score: 1.0\n",
      "current step: 591/1000, score: 1.0\n",
      "current step: 592/1000, score: 1.0\n",
      "current step: 593/1000, score: 1.0\n",
      "current step: 594/1000, score: 1.0\n",
      "current step: 595/1000, score: 1.0\n",
      "current step: 596/1000, score: 1.0\n",
      "current step: 597/1000, score: 1.0\n",
      "current step: 598/1000, score: 1.0\n",
      "current step: 599/1000, score: 1.0\n",
      "current step: 600/1000, score: 1.0\n",
      "current step: 601/1000, score: 1.0\n",
      "current step: 602/1000, score: 1.0\n",
      "current step: 603/1000, score: 1.0\n",
      "current step: 604/1000, score: 1.0\n",
      "current step: 605/1000, score: 1.0\n",
      "current step: 606/1000, score: 1.0\n",
      "current step: 607/1000, score: 1.0\n",
      "current step: 608/1000, score: 1.0\n",
      "current step: 609/1000, score: 1.0\n",
      "current step: 610/1000, score: 1.0\n",
      "current step: 611/1000, score: 1.0\n",
      "current step: 612/1000, score: 1.0\n",
      "current step: 613/1000, score: 1.0\n",
      "current step: 614/1000, score: 1.0\n",
      "current step: 615/1000, score: 1.0\n",
      "current step: 616/1000, score: 1.0\n",
      "current step: 617/1000, score: 1.0\n",
      "current step: 618/1000, score: 1.0\n",
      "current step: 619/1000, score: 1.0\n",
      "current step: 620/1000, score: 1.0\n",
      "current step: 621/1000, score: 1.0\n",
      "current step: 622/1000, score: 1.0\n",
      "current step: 623/1000, score: 1.0\n",
      "current step: 624/1000, score: 1.0\n",
      "current step: 625/1000, score: 1.0\n",
      "current step: 626/1000, score: 1.0\n",
      "current step: 627/1000, score: 1.0\n",
      "current step: 628/1000, score: 1.0\n",
      "current step: 629/1000, score: 1.0\n",
      "current step: 630/1000, score: 1.0\n",
      "current step: 631/1000, score: 1.0\n",
      "current step: 632/1000, score: 1.0\n",
      "current step: 633/1000, score: 1.0\n",
      "current step: 634/1000, score: 1.0\n",
      "current step: 635/1000, score: 1.0\n",
      "current step: 636/1000, score: 1.0\n",
      "current step: 637/1000, score: 1.0\n",
      "current step: 638/1000, score: 1.0\n",
      "current step: 639/1000, score: 1.0\n",
      "current step: 640/1000, score: 1.0\n",
      "current step: 641/1000, score: 1.0\n",
      "current step: 642/1000, score: 1.0\n",
      "current step: 643/1000, score: 1.0\n",
      "current step: 644/1000, score: 1.0\n",
      "current step: 645/1000, score: 1.0\n",
      "current step: 646/1000, score: 1.0\n",
      "current step: 647/1000, score: 1.0\n",
      "current step: 648/1000, score: 1.0\n",
      "current step: 649/1000, score: 1.0\n",
      "current step: 650/1000, score: 1.0\n",
      "current step: 651/1000, score: 1.0\n",
      "current step: 652/1000, score: 1.0\n",
      "current step: 653/1000, score: 1.0\n",
      "current step: 654/1000, score: 1.0\n",
      "current step: 655/1000, score: 1.0\n",
      "current step: 656/1000, score: 1.0\n",
      "current step: 657/1000, score: 1.0\n",
      "current step: 658/1000, score: 1.0\n",
      "current step: 659/1000, score: 1.0\n",
      "current step: 660/1000, score: 1.0\n",
      "current step: 661/1000, score: 1.0\n",
      "current step: 662/1000, score: 1.0\n",
      "current step: 663/1000, score: 1.0\n",
      "current step: 664/1000, score: 1.0\n",
      "current step: 665/1000, score: 1.0\n",
      "current step: 666/1000, score: 1.0\n",
      "current step: 667/1000, score: 1.0\n",
      "current step: 668/1000, score: 1.0\n",
      "current step: 669/1000, score: 1.0\n",
      "current step: 670/1000, score: 1.0\n",
      "current step: 671/1000, score: 1.0\n",
      "current step: 672/1000, score: 1.0\n",
      "current step: 673/1000, score: 1.0\n",
      "current step: 674/1000, score: 1.0\n",
      "current step: 675/1000, score: 1.0\n",
      "current step: 676/1000, score: 1.0\n",
      "current step: 677/1000, score: 1.0\n",
      "current step: 678/1000, score: 1.0\n",
      "current step: 679/1000, score: 1.0\n",
      "current step: 680/1000, score: 1.0\n",
      "current step: 681/1000, score: 1.0\n",
      "current step: 682/1000, score: 1.0\n",
      "current step: 683/1000, score: 1.0\n",
      "current step: 684/1000, score: 1.0\n",
      "current step: 685/1000, score: 1.0\n",
      "current step: 686/1000, score: 1.0\n",
      "current step: 687/1000, score: 1.0\n",
      "current step: 688/1000, score: 1.0\n",
      "current step: 689/1000, score: 1.0\n",
      "current step: 690/1000, score: 1.0\n",
      "current step: 691/1000, score: 1.0\n",
      "current step: 692/1000, score: 1.0\n",
      "current step: 693/1000, score: 1.0\n",
      "current step: 694/1000, score: 1.0\n",
      "current step: 695/1000, score: 1.0\n",
      "current step: 696/1000, score: 1.0\n",
      "current step: 697/1000, score: 1.0\n",
      "current step: 698/1000, score: 1.0\n",
      "current step: 699/1000, score: 1.0\n",
      "current step: 700/1000, score: 1.0\n",
      "current step: 701/1000, score: 1.0\n",
      "current step: 702/1000, score: 1.0\n",
      "current step: 703/1000, score: 1.0\n",
      "current step: 704/1000, score: 1.0\n",
      "current step: 705/1000, score: 1.0\n",
      "current step: 706/1000, score: 1.0\n",
      "current step: 707/1000, score: 1.0\n",
      "current step: 708/1000, score: 1.0\n",
      "current step: 709/1000, score: 1.0\n",
      "current step: 710/1000, score: 1.0\n",
      "current step: 711/1000, score: 1.0\n",
      "current step: 712/1000, score: 1.0\n",
      "current step: 713/1000, score: 1.0\n",
      "current step: 714/1000, score: 1.0\n",
      "current step: 715/1000, score: 1.0\n",
      "current step: 716/1000, score: 1.0\n",
      "current step: 717/1000, score: 1.0\n",
      "current step: 718/1000, score: 1.0\n",
      "current step: 719/1000, score: 1.0\n",
      "current step: 720/1000, score: 1.0\n",
      "current step: 721/1000, score: 1.0\n",
      "current step: 722/1000, score: 1.0\n",
      "current step: 723/1000, score: 1.0\n",
      "current step: 724/1000, score: 1.0\n",
      "current step: 725/1000, score: 1.0\n",
      "current step: 726/1000, score: 1.0\n",
      "current step: 727/1000, score: 1.0\n",
      "current step: 728/1000, score: 1.0\n",
      "current step: 729/1000, score: 1.0\n",
      "current step: 730/1000, score: 1.0\n",
      "current step: 731/1000, score: 1.0\n",
      "current step: 732/1000, score: 1.0\n",
      "current step: 733/1000, score: 1.0\n",
      "current step: 734/1000, score: 1.0\n",
      "current step: 735/1000, score: 1.0\n",
      "current step: 736/1000, score: 1.0\n",
      "current step: 737/1000, score: 1.0\n",
      "current step: 738/1000, score: 1.0\n",
      "current step: 739/1000, score: 1.0\n",
      "current step: 740/1000, score: 1.0\n",
      "current step: 741/1000, score: 1.0\n",
      "current step: 742/1000, score: 1.0\n",
      "current step: 743/1000, score: 1.0\n",
      "current step: 744/1000, score: 1.0\n",
      "current step: 745/1000, score: 1.0\n",
      "current step: 746/1000, score: 1.0\n",
      "current step: 747/1000, score: 1.0\n",
      "current step: 748/1000, score: 1.0\n",
      "current step: 749/1000, score: 1.0\n",
      "current step: 750/1000, score: 1.0\n",
      "current step: 751/1000, score: 1.0\n",
      "current step: 752/1000, score: 1.0\n",
      "current step: 753/1000, score: 1.0\n",
      "current step: 754/1000, score: 1.0\n",
      "current step: 755/1000, score: 1.0\n",
      "current step: 756/1000, score: 1.0\n",
      "current step: 757/1000, score: 1.0\n",
      "current step: 758/1000, score: 1.0\n",
      "current step: 759/1000, score: 1.0\n",
      "current step: 760/1000, score: 1.0\n",
      "current step: 761/1000, score: 1.0\n",
      "current step: 762/1000, score: 1.0\n",
      "current step: 763/1000, score: 1.0\n",
      "current step: 764/1000, score: 1.0\n",
      "current step: 765/1000, score: 1.0\n",
      "current step: 766/1000, score: 1.0\n",
      "current step: 767/1000, score: 1.0\n",
      "current step: 768/1000, score: 1.0\n",
      "current step: 769/1000, score: 1.0\n",
      "current step: 770/1000, score: 1.0\n",
      "current step: 771/1000, score: 1.0\n",
      "current step: 772/1000, score: 1.0\n",
      "current step: 773/1000, score: 1.0\n",
      "current step: 774/1000, score: 1.0\n",
      "current step: 775/1000, score: 1.0\n",
      "current step: 776/1000, score: 1.0\n",
      "current step: 777/1000, score: 1.0\n",
      "current step: 778/1000, score: 1.0\n",
      "current step: 779/1000, score: 1.0\n",
      "current step: 780/1000, score: 1.0\n",
      "current step: 781/1000, score: 1.0\n",
      "current step: 782/1000, score: 1.0\n",
      "current step: 783/1000, score: 1.0\n",
      "current step: 784/1000, score: 1.0\n",
      "current step: 785/1000, score: 1.0\n",
      "current step: 786/1000, score: 1.0\n",
      "current step: 787/1000, score: 1.0\n",
      "current step: 788/1000, score: 1.0\n",
      "current step: 789/1000, score: 1.0\n",
      "current step: 790/1000, score: 1.0\n",
      "current step: 791/1000, score: 1.0\n",
      "current step: 792/1000, score: 1.0\n",
      "current step: 793/1000, score: 1.0\n",
      "current step: 794/1000, score: 1.0\n",
      "current step: 795/1000, score: 1.0\n",
      "current step: 796/1000, score: 1.0\n",
      "current step: 797/1000, score: 1.0\n",
      "current step: 798/1000, score: 1.0\n",
      "current step: 799/1000, score: 1.0\n",
      "current step: 800/1000, score: 1.0\n",
      "current step: 801/1000, score: 1.0\n",
      "current step: 802/1000, score: 1.0\n",
      "current step: 803/1000, score: 1.0\n",
      "current step: 804/1000, score: 1.0\n",
      "current step: 805/1000, score: 1.0\n",
      "current step: 806/1000, score: 1.0\n",
      "current step: 807/1000, score: 1.0\n",
      "current step: 808/1000, score: 1.0\n",
      "current step: 809/1000, score: 1.0\n",
      "current step: 810/1000, score: 1.0\n",
      "current step: 811/1000, score: 1.0\n",
      "current step: 812/1000, score: 1.0\n",
      "current step: 813/1000, score: 1.0\n",
      "current step: 814/1000, score: 1.0\n",
      "current step: 815/1000, score: 1.0\n",
      "current step: 816/1000, score: 1.0\n",
      "current step: 817/1000, score: 1.0\n",
      "current step: 818/1000, score: 1.0\n",
      "current step: 819/1000, score: 1.0\n",
      "current step: 820/1000, score: 1.0\n",
      "current step: 821/1000, score: 1.0\n",
      "current step: 822/1000, score: 1.0\n",
      "current step: 823/1000, score: 1.0\n",
      "current step: 824/1000, score: 1.0\n",
      "current step: 825/1000, score: 1.0\n",
      "current step: 826/1000, score: 1.0\n",
      "current step: 827/1000, score: 1.0\n",
      "current step: 828/1000, score: 1.0\n",
      "current step: 829/1000, score: 1.0\n",
      "current step: 830/1000, score: 1.0\n",
      "current step: 831/1000, score: 1.0\n",
      "current step: 832/1000, score: 1.0\n",
      "current step: 833/1000, score: 1.0\n",
      "current step: 834/1000, score: 1.0\n",
      "current step: 835/1000, score: 1.0\n",
      "current step: 836/1000, score: 1.0\n",
      "current step: 837/1000, score: 1.0\n",
      "current step: 838/1000, score: 1.0\n",
      "current step: 839/1000, score: 1.0\n",
      "current step: 840/1000, score: 1.0\n",
      "current step: 841/1000, score: 1.0\n",
      "current step: 842/1000, score: 1.0\n",
      "current step: 843/1000, score: 1.0\n",
      "current step: 844/1000, score: 1.0\n",
      "current step: 845/1000, score: 1.0\n",
      "current step: 846/1000, score: 1.0\n",
      "current step: 847/1000, score: 1.0\n",
      "current step: 848/1000, score: 1.0\n",
      "current step: 849/1000, score: 1.0\n",
      "current step: 850/1000, score: 1.0\n",
      "current step: 851/1000, score: 1.0\n",
      "current step: 852/1000, score: 1.0\n",
      "current step: 853/1000, score: 1.0\n",
      "current step: 854/1000, score: 1.0\n",
      "current step: 855/1000, score: 1.0\n",
      "current step: 856/1000, score: 1.0\n",
      "current step: 857/1000, score: 1.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "current step: 858/1000, score: 1.0\n",
      "current step: 859/1000, score: 1.0\n",
      "current step: 860/1000, score: 1.0\n",
      "current step: 861/1000, score: 1.0\n",
      "current step: 862/1000, score: 1.0\n",
      "current step: 863/1000, score: 1.0\n",
      "current step: 864/1000, score: 1.0\n",
      "current step: 865/1000, score: 1.0\n",
      "current step: 866/1000, score: 1.0\n",
      "current step: 867/1000, score: 1.0\n",
      "current step: 868/1000, score: 1.0\n",
      "current step: 869/1000, score: 1.0\n",
      "current step: 870/1000, score: 1.0\n",
      "current step: 871/1000, score: 1.0\n",
      "current step: 872/1000, score: 1.0\n",
      "current step: 873/1000, score: 1.0\n",
      "current step: 874/1000, score: 1.0\n",
      "current step: 875/1000, score: 1.0\n",
      "current step: 876/1000, score: 1.0\n",
      "current step: 877/1000, score: 1.0\n",
      "current step: 878/1000, score: 1.0\n",
      "current step: 879/1000, score: 1.0\n",
      "current step: 880/1000, score: 1.0\n",
      "current step: 881/1000, score: 1.0\n",
      "current step: 882/1000, score: 1.0\n",
      "current step: 883/1000, score: 1.0\n",
      "current step: 884/1000, score: 1.0\n",
      "current step: 885/1000, score: 1.0\n",
      "current step: 886/1000, score: 1.0\n",
      "current step: 887/1000, score: 1.0\n",
      "current step: 888/1000, score: 1.0\n",
      "current step: 889/1000, score: 1.0\n",
      "current step: 890/1000, score: 1.0\n",
      "current step: 891/1000, score: 1.0\n",
      "current step: 892/1000, score: 1.0\n",
      "current step: 893/1000, score: 1.0\n",
      "current step: 894/1000, score: 1.0\n",
      "current step: 895/1000, score: 1.0\n",
      "current step: 896/1000, score: 1.0\n",
      "current step: 897/1000, score: 1.0\n",
      "current step: 898/1000, score: 1.0\n",
      "current step: 899/1000, score: 1.0\n",
      "current step: 900/1000, score: 1.0\n",
      "current step: 901/1000, score: 1.0\n",
      "current step: 902/1000, score: 1.0\n",
      "current step: 903/1000, score: 1.0\n",
      "current step: 904/1000, score: 1.0\n",
      "current step: 905/1000, score: 1.0\n",
      "current step: 906/1000, score: 1.0\n",
      "current step: 907/1000, score: 1.0\n",
      "current step: 908/1000, score: 1.0\n",
      "current step: 909/1000, score: 1.0\n",
      "current step: 910/1000, score: 1.0\n",
      "current step: 911/1000, score: 1.0\n",
      "current step: 912/1000, score: 1.0\n",
      "current step: 913/1000, score: 1.0\n",
      "current step: 914/1000, score: 1.0\n",
      "current step: 915/1000, score: 1.0\n",
      "current step: 916/1000, score: 1.0\n",
      "current step: 917/1000, score: 1.0\n",
      "current step: 918/1000, score: 1.0\n",
      "current step: 919/1000, score: 1.0\n",
      "current step: 920/1000, score: 1.0\n",
      "current step: 921/1000, score: 1.0\n",
      "current step: 922/1000, score: 1.0\n",
      "current step: 923/1000, score: 1.0\n",
      "current step: 924/1000, score: 1.0\n",
      "current step: 925/1000, score: 1.0\n",
      "current step: 926/1000, score: 1.0\n",
      "current step: 927/1000, score: 1.0\n",
      "current step: 928/1000, score: 1.0\n",
      "current step: 929/1000, score: 1.0\n",
      "current step: 930/1000, score: 1.0\n",
      "current step: 931/1000, score: 1.0\n",
      "current step: 932/1000, score: 1.0\n",
      "current step: 933/1000, score: 1.0\n",
      "current step: 934/1000, score: 1.0\n",
      "current step: 935/1000, score: 1.0\n",
      "current step: 936/1000, score: 1.0\n",
      "current step: 937/1000, score: 1.0\n",
      "current step: 938/1000, score: 1.0\n",
      "current step: 939/1000, score: 1.0\n",
      "current step: 940/1000, score: 1.0\n",
      "current step: 941/1000, score: 1.0\n",
      "current step: 942/1000, score: 1.0\n",
      "current step: 943/1000, score: 1.0\n",
      "current step: 944/1000, score: 1.0\n",
      "current step: 945/1000, score: 1.0\n",
      "current step: 946/1000, score: 1.0\n",
      "current step: 947/1000, score: 1.0\n",
      "current step: 948/1000, score: 1.0\n",
      "current step: 949/1000, score: 1.0\n",
      "current step: 950/1000, score: 1.0\n",
      "current step: 951/1000, score: 1.0\n",
      "current step: 952/1000, score: 1.0\n",
      "current step: 953/1000, score: 1.0\n",
      "current step: 954/1000, score: 1.0\n",
      "current step: 955/1000, score: 1.0\n",
      "current step: 956/1000, score: 1.0\n",
      "current step: 957/1000, score: 1.0\n",
      "current step: 958/1000, score: 1.0\n",
      "current step: 959/1000, score: 1.0\n",
      "current step: 960/1000, score: 1.0\n",
      "current step: 961/1000, score: 1.0\n",
      "current step: 962/1000, score: 1.0\n",
      "current step: 963/1000, score: 1.0\n",
      "current step: 964/1000, score: 1.0\n",
      "current step: 965/1000, score: 1.0\n",
      "current step: 966/1000, score: 1.0\n",
      "current step: 967/1000, score: 1.0\n",
      "current step: 968/1000, score: 1.0\n",
      "current step: 969/1000, score: 1.0\n",
      "current step: 970/1000, score: 1.0\n",
      "current step: 971/1000, score: 1.0\n",
      "current step: 972/1000, score: 1.0\n",
      "current step: 973/1000, score: 1.0\n",
      "current step: 974/1000, score: 1.0\n",
      "current step: 975/1000, score: 1.0\n",
      "current step: 976/1000, score: 1.0\n",
      "current step: 977/1000, score: 1.0\n",
      "current step: 978/1000, score: 1.0\n",
      "current step: 979/1000, score: 1.0\n",
      "current step: 980/1000, score: 1.0\n",
      "current step: 981/1000, score: 1.0\n",
      "current step: 982/1000, score: 1.0\n",
      "current step: 983/1000, score: 1.0\n",
      "current step: 984/1000, score: 1.0\n",
      "current step: 985/1000, score: 1.0\n",
      "current step: 986/1000, score: 1.0\n",
      "current step: 987/1000, score: 1.0\n",
      "current step: 988/1000, score: 1.0\n",
      "current step: 989/1000, score: 1.0\n",
      "current step: 990/1000, score: 1.0\n",
      "current step: 991/1000, score: 1.0\n",
      "current step: 992/1000, score: 1.0\n",
      "current step: 993/1000, score: 1.0\n",
      "current step: 994/1000, score: 1.0\n",
      "current step: 995/1000, score: 1.0\n",
      "current step: 996/1000, score: 1.0\n",
      "current step: 997/1000, score: 1.0\n",
      "current step: 998/1000, score: 1.0\n",
      "current step: 999/1000, score: 1.0\n"
     ]
    }
   ],
   "source": [
    "# make it as a funtion for data analysis\n",
    "\n",
    "\n",
    "agent = Agent(\n",
    "    action_dim=env.action_space.n,\n",
    "    state_dim=env.observation_space.n,\n",
    "    alpha=0.2,\n",
    "    gamma=0.9,\n",
    "    epsilon=0.5)\n",
    "\n",
    "# training\n",
    "score_queue = []\n",
    "\n",
    "for k in range(cfg_params[\"max_train_steps\"]):\n",
    "    # reset t  he s_k\n",
    "    data_queue = []\n",
    "    s_k, info = env.reset(seed=cfg_params[\"random_seed\"])\n",
    "    # collect data set\n",
    "    for ek in range(cfg_params[\"max_episode_steps\"]):\n",
    "        a_k = agent.select_action(s_k)\n",
    "        s_k1, r_k, terminated, truncated, info = env.step(a_k)\n",
    "        data_queue.append([s_k, a_k, r_k])\n",
    "        if terminated:\n",
    "#             print(f\"s_k: {s_k}, s_k1: {s_k1}, r_k: {r_k}, a_k: {a_k}, e_k : {ek}, terminated: {terminated}\")\n",
    "            break\n",
    "        s_k = s_k1\n",
    "    \n",
    "    agent.MonteCarlo_train(data_queue)\n",
    "\n",
    "    score = evaluate_policy(env, agent)\n",
    "    score_queue.append(score)\n",
    "    print(f'current step: {k}/{cfg_params[\"max_train_steps\"]}, score: {score}')\n",
    "\n",
    "# if render:\n",
    "#     evaluate_env = gym.make(cfg_params[\"env_name\"], render_mode=\"human\")\n",
    "#     for _ in range(1):\n",
    "#         evaluate_policy(evaluate_env, agent)\n",
    "#     evaluate_env.close()\n",
    "# print(Returns)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "577466d2",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'main_function' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[64], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# play and render\u001b[39;00m\n\u001b[1;32m      2\u001b[0m plt\u001b[38;5;241m.\u001b[39mfigure()\n\u001b[0;32m----> 3\u001b[0m score_queue \u001b[38;5;241m=\u001b[39m main_function(alpha \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.2\u001b[39m, gamma\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.9\u001b[39m, render\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m      5\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(score_queue, label\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mQ\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      7\u001b[0m plt\u001b[38;5;241m.\u001b[39mylabel(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mscore\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'main_function' is not defined"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# play and render\n",
    "plt.figure()\n",
    "score_queue = main_function(alpha = 0.2, gamma=0.9, render=True)\n",
    "evaluate_policy\n",
    "plt.plot(score_queue, label=\"Q\")\n",
    "\n",
    "plt.ylabel('score')\n",
    "plt.xlabel('step')\n",
    "plt.title('Q-Learning')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3942317b",
   "metadata": {},
   "outputs": [],
   "source": [
    "evaluate_env = gym.make(cfg_params[\"env_name\"], render_mode=\"human\",desc=None, map_name=\"4x4\", is_slippery=True)\n",
    "for i in range(10):\n",
    "    evaluate_policy(evaluate_env, agent)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d24b46a2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}