Tic_Tac_Toe_RL_Assingment_01.ipynb

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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import random\n",
        "\n",
        "# Define the Tic-Tac-Toe board\n",
        "board = np.array([[' ' for _ in range(3)] for _ in range(3)])\n",
        "\n",
        "# Define the Q-Learning agent's Q-table\n",
        "Q = {}\n",
        "\n",
        "# Define hyperparameters\n",
        "learning_rate = 0.8\n",
        "discount_factor = 1.0\n",
        "exploration_prob = 0.2\n",
        "epochs = 50000\n",
        "\n",
        "# Function to check if a player has won\n",
        "def check_win(player, board):\n",
        "    for i in range(3):\n",
        "        if all(board[i, :] == player) or all(board[:, i] == player):\n",
        "            return True\n",
        "    if all(np.diag(board) == player) or all(np.diag(np.fliplr(board)) == player):\n",
        "        return True\n",
        "    return False\n",
        "\n",
        "# Function to get a list of available moves\n",
        "def available_moves(board):\n",
        "    return [(i, j) for i in range(3) for j in range(3) if board[i, j] == ' ']\n",
        "\n",
        "# Function to choose a move for the Q-Learning agent\n",
        "def choose_move(board):\n",
        "    if random.uniform(0, 1) < exploration_prob:\n",
        "        return random.choice(available_moves(board))\n",
        "    else:\n",
        "        max_q = -float('inf')\n",
        "        best_move = None\n",
        "        for move in available_moves(board):\n",
        "            next_board = board.copy()\n",
        "            next_board[move] = 'O'\n",
        "            next_state = tuple(map(tuple, next_board))\n",
        "            if next_state not in Q:\n",
        "                Q[next_state] = 0\n",
        "            if Q[next_state] > max_q:\n",
        "                max_q = Q[next_state]\n",
        "                best_move = move\n",
        "        return best_move\n",
        "\n",
        "# Function to train the Q-Learning agent\n",
        "def train_agent():\n",
        "    for _ in range(epochs):\n",
        "        board = np.array([[' ' for _ in range(3)] for _ in range(3)])\n",
        "        state_history = []\n",
        "\n",
        "        while True:\n",
        "            move = choose_move(board)\n",
        "            state_history.append(tuple(map(tuple, board)))\n",
        "            board[move] = 'O'\n",
        "\n",
        "            if check_win('O', board):\n",
        "                reward = 1\n",
        "                break\n",
        "            elif len(available_moves(board)) == 0:\n",
        "                reward = 0\n",
        "                break\n",
        "\n",
        "            opponent_move = random.choice(available_moves(board))\n",
        "            board[opponent_move] = 'X'\n",
        "\n",
        "            if check_win('X', board):\n",
        "                reward = -1\n",
        "                break\n",
        "\n",
        "        for state in state_history:\n",
        "            if state not in Q:\n",
        "                Q[state] = 0\n",
        "            Q[state] += learning_rate * (reward - Q[state])\n",
        "\n",
        "# Function to play the game\n",
        "def play_game():\n",
        "    board = np.array([[' ' for _ in range(3)] for _ in range(3)])\n",
        "    while True:\n",
        "        print(board)\n",
        "        row = int(input(\"Enter the row (0, 1, 2): \"))\n",
        "        col = int(input(\"Enter the column (0, 1, 2): \"))\n",
        "        if (row, col) not in available_moves(board):\n",
        "            print(\"Invalid move. Try again.\")\n",
        "            continue\n",
        "        board[(row, col)] = 'X'\n",
        "\n",
        "        if check_win('X', board):\n",
        "            print(board)\n",
        "            print(\"You win!\")\n",
        "            break\n",
        "\n",
        "        move = choose_move(board)\n",
        "        print(f\"Agent chooses: {move}\")\n",
        "        board[move] = 'O'\n",
        "\n",
        "        if check_win('O', board):\n",
        "            print(board)\n",
        "            print(\"Agent wins!\")\n",
        "            break\n",
        "\n",
        "        if len(available_moves(board)) == 0:\n",
        "            print(board)\n",
        "            print(\"It's a draw!\")\n",
        "            break\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "    train_agent()\n",
        "    play_game()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_FAHIITWNxu7",
        "outputId": "c3defabc-6aa0-42ce-f9b7-874268ad2f8c"
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      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[' ' ' ' ' ']\n",
            " [' ' ' ' ' ']\n",
            " [' ' ' ' ' ']]\n",
            "Enter the row (0, 1, 2): 0\n",
            "Enter the column (0, 1, 2): 0\n",
            "Agent chooses: (2, 2)\n",
            "[['X' ' ' ' ']\n",
            " [' ' ' ' ' ']\n",
            " [' ' ' ' 'O']]\n",
            "Enter the row (0, 1, 2): 1\n",
            "Enter the column (0, 1, 2): 0\n",
            "Agent chooses: (2, 0)\n",
            "[['X' ' ' ' ']\n",
            " ['X' ' ' ' ']\n",
            " ['O' ' ' 'O']]\n",
            "Enter the row (0, 1, 2): 0\n",
            "Enter the column (0, 1, 2): 1\n",
            "Agent chooses: (0, 2)\n",
            "[['X' 'X' 'O']\n",
            " ['X' ' ' ' ']\n",
            " ['O' ' ' 'O']]\n",
            "Enter the row (0, 1, 2): 1\n",
            "Enter the column (0, 1, 2): 2\n",
            "Agent chooses: (1, 1)\n",
            "[['X' 'X' 'O']\n",
            " ['X' 'O' 'X']\n",
            " ['O' ' ' 'O']]\n",
            "Agent wins!\n"
          ]
        }
      ]
    }
  ]
}