Main.py

from utils.tenhouconnection import Connection
import gym
from QLearning import QLearning as QLe
from gym_mahjong.envs.mahjong_his_env import MahjongEnv

def play():
    env = gym.envs.make('Mahjong-v0')
    QL = QLe(env)
    connection = Connection(QL)
    connection.connect()
    auth = connection.authencate()
    print(auth)
    if auth:
        connection.play()
    else:
        connection.end()

# def train_and_play():
#     env = gym.envs.make('Mahjong-v0')
#     QL = QLe(env)
#     validation = []
#     for episode in range(300):
#         observation = env.reset_()
#         while True:
#             action = QL.decision(observation)
#             observation_after, reward, finish, validate = env.step(action)
#             QL.toHistory(observation, action, reward, observation_after)
#             validation.append(validate)
#             if (episode > 200) and (episode % 5 == 0):
#                 QL.learn()
#                 # print('Learned!')
#
#             observation = observation_after
#
#             if finish:
#                 break
#     connection = Connection(QL)
#
#
#     connection.connect()
#     auth = connection.authencate()
#     print(auth)
#     if auth:
#         connection.play()
#     else:
#         connection.end()



if __name__ == '__main__':
    play()