gym-tic-tac-toe/gym_tic_tac_toe/envs/tic_tac_toe_env.py

import gym
from gym import spaces
import numpy as np

class TicTacToeEnv(gym.Env):
    metadata = {'render.modes': ['human']}

    def __init__(self):
        self.action_space = spaces.Tuple((spaces.Discrete(2), spaces.Discrete(9)))
        self.observation_space = spaces.Discrete(3)#Tuple(spaces.Discrete(3), spaces.Discrete(9))
    def _step(self, action):
        done = False
        reward = 0

        p, square = action
        
       # p = p*2 - 1
        # check move legality
        proposed = self.state['board'][square]
        om = self.state['on_move']
        print ("on move: ", om)
        if (proposed != 0): # wrong player, not empty
            print("illegal move ", action, ". (square occupied): ", square)
            done = True
            reward = -2 * om # player who did NOT make the illegal move
        if (p != om): # wrong player, not empty
            print("illegal move  ", action, " not on move: ", p)
            done = True
            reward = -2 * om # player who did NOT make the illegal move
        else:
            self.state['board'][square] = p
            self.state['on_move'] = -p

        # check game over
        for i in range(3):
            if (self.state['board'][i * 3] == p and self.state['board'][i*3 + 1] == p and self.state['board'][i*3+2] == 2):
                reward = p
                done = True
                break
            #TODO other cases
                
        return np.array(self.state), reward, done, {}
    def _reset(self):
        self.state = {}
        self.state['board'] = [0,0,0,0,0,0,0,0,0]
        self.state['on_move'] = 1
        return self.state
    def _render(self, mode='human', close=False):
        if close:
            return
        print("on move: " , self.state['on_move'])
        for i in range (9):
            print (self.state['board'][i], end=" ")
        print()
    def move_generator(self):
        moves = []
        for i in range (9):
            
            if (self.state['board'][i]== 0):
                p = self.state['on_move']
                m = [p, i]
                moves.append(m)
        return moves