state = doom.get_current_state()
action_index = doomguy.act(state)
next_state, reward, done = doom.step(action_index)
doomguy.remember(state, action_index, reward, next_state, done)
step += 1
loss = doomguy.train()
doomguy.reset_memory()
print('Total steps: {}, loss was: {}'.format(step, loss))
if show_results:
doom = VizdoomWrapper(config_path=config_path,
reward_table=reward_table,
frame_resolution=resolution,
show_mode=True,
frame_stack=4)
for episode in range(3):
doom.new_game()
done = False
while not done:
state = doom.get_current_state()
action_index = doomguy.act(state)
done = doom.set_action(action_index)
# Sleep between episodes
sleep(1.0)
score = doom.get_total_reward()
print('Total score: {}'.format(score))
episodes_to_watch = 2
print('Initialising VizDoom...')
config_path = 'scenarios/basic.cfg'
actor_path = 'models/defend_the_center_actor.hd5'
critic_path = 'models/defend_the_center_critic.hd5'
reward_table = OrderedDict({'FRAGCOUNT': 1})
resolution = (90, 60)
doom = VizdoomWrapper(config_path=config_path,
reward_table=reward_table,
frame_resolution=resolution,
show_mode=True,
frame_stack=1)
print('Initialising Doomguy...')
doomguy = BaseQDoom(doom.get_state_size(), doom.get_action_size())
doomguy.load_model()
for _ in range(episodes_to_watch):
done = False
doom.new_game()
while not done:
state = doom.get_current_state()
best_action = doomguy.act(state)
done = doom.set_action(best_action)
# Sleep between episodes
sleep(1.0)
score = doom.get_total_reward()
print('Total score: {}'.format(score))