from osero import Osero
env = Osero(board_size=6)
exit()
from logger import EpisodeLogger
from model import NetworkModel
from keras.optimizers import Adam
from rl.agents.dqn import DQNAgent
from rl.policy import EpsGreedyQPolicy
from rl.memory import SequentialMemory
env = Osero(board_size=4)
nb_actions = env.action_space.n
model = NetworkModel.create_simple_nn(env)
print(model.summary())
memory = SequentialMemory(limit=10000, window_length=1)
policy = EpsGreedyQPolicy(eps=0.1)
dqn = DQNAgent(model=model,
nb_actions=nb_actions,
memory=memory,
nb_steps_warmup=100,
target_model_update=1e-2,
policy=policy)
dqn.compile(Adam(lr=1e-3), metrics=['mae'])
# dqn.load_weights('results/190621/10000.h5')
history = dqn.fit(env,
nb_steps=10000,
