def __init__(self,
state_size,
action_size,
force_continue=False,
load_weights=False):
BaseAgent.__init__(self)
self._state_size = state_size
self._action_size = action_size
self._gamma = 0.95
self._epsilon = 1.0 if not force_continue else 0.01
self._epsilon_decay = 0.995
self._epsilon_min = 0.01
self._learning_rate = 0.001
self._model = None
self._build_model()
# Load up known weights
max_file_number = 0
if load_weights or force_continue:
for file in os.listdir('models'):
file_without_ending = file.split('.')[0]
file_number = file_without_ending.split('_')[1]
if int(file_number) > int(max_file_number):
max_file_number = int(file_number)
file_loaded = 'weights_' + '0' + str(max_file_number) + '.hdf5'
file_loaded = os.path.join('models', file_loaded)
print("Loading file " + str(file_loaded) +
" to continue training.")
self.load(file_loaded)
self.restart_file_number_offset = max_file_number
def __init__(self, state_size, action_size, load_weights=False):
BaseAgent.__init__(self)
self._state_size = state_size
self._action_size = action_size
self._gamma = 0.95
self._epsilon = 1.0
self._epsilon_decay = 0.995
self._epsilon_min = 0.01
self._learning_rate = 0.001
self._model = None
self._build_model()
# Load up known weights
max_file_number = ''
if load_weights:
for file in os.listdir('/models'):
file_without_ending = file.split('.')[0]
file_number = file_without_ending.split('_')[1]
if int(file_number) > int(max_file_number):
max_file_number = file_number
self.load(os.path.join('models', 'weights_' + max_file_number + '.hdf5'))
def __init__(self):
BaseAgent.__init__(self)
self._first_shot = True
self._last_shot_pwr = 0
self._last_shot_ang = 0
self._target_pwr = 0
self._target_ang = 0
self._distance_to_target = 1024
self._last_impact = [0, 0]
self._ready_to_fire = True
self._exploration_value = 10