Training code for tic tac toe solver

tic_tac_toe_player_trainer.py

bot1_sym = 'O'
bot2_sym = 'X'

def optimize_bot(game, bot1, bot2):
    """
    Punish or Reward the bot with respect to the agent that wins the game
    """
    if game.winner == bot1_sym:
        bot1.on_reward(1)
        # reward
        bot2.on_reward(-1)
        # punishment
    elif game.winner == bot2_sym:
        bot1.on_reward(-1)
        bot2.on_reward(1)

def train(epochs, bot1, bot2):
    bot1_wins = 0
    bot2_wins = 0
    win_trace = pd.DataFrame(data=np.zeros((epochs, 2)), columns=['bot1', 'bot2'])
    for i in range(epochs):
        print('-' * 100)
        print('epoch: {}'.format(i + 1))
        game = Board()
        while not game.stale:
            # Exit if the board is full
            winner = game.player_move(bot1_sym, *bot1.select_move(game.board))
            # Check if the move results in a winner 
            # winner = None if no one wins,
            # winner = 'draw' if no one can win
            if winner:
                optimize_bot(game, bot1, bot2)
                # reward the winner
                bot1_wins += 1
                win_trace.set_value(i, 'bot1', 1)
                break
            elif winner == 'draw':
                break
            winner = game.player_move(bot2_sym, *bot2.select_move(game.board))
            if winner:
                optimize_bot(game, bot1, bot2)
                bot2_wins += 1
                win_trace.set_value(i, 'bot2', 1)
                break
                win_trace[i] = 2
            elif winner == 'draw':
                break
    return win_trace, bot1_wins, bot2_wins