def test_action(self, obs):
self.controller.current_state = handcraft_function.get_all_observation(obs)
state = self.controller.current_state
action_and_parameter = self.controller.network.action(state)
macro_and_parameter = handcraft_function.reflect(obs, action_and_parameter)
action = handcraft_function.assembly_action(obs, self.index, macro_and_parameter)
return action
def test_action(self, obs):
# self.controller.current_state = handcraft_function_for_level_2_attack_controller.get_raw_units_observation(obs)
self.controller.current_state = handcraft_function.get_all_observation(
obs)
state = self.controller.current_state
action_and_parameter = self.controller.network.action(state)
macro_and_parameter = handcraft_function.reflect(
len(sa.attack_controller), action_and_parameter)
action = handcraft_function.assembly_action(obs, self.index,
macro_and_parameter)
return action
def train_action(self, obs):
self.top_decision_maker.current_state = handcraft_function.get_all_observation(
obs)
if self.top_decision_maker.previous_action is not None:
self.top_decision_maker.network.perceive(
self.top_decision_maker.previous_state,
self.top_decision_maker.previous_action,
self.top_decision_maker.previous_reward,
self.top_decision_maker.current_state, obs.last())
controller_number = self.top_decision_maker.network.egreedy_action(
self.top_decision_maker.current_state)
self.top_decision_maker.previous_reward = obs.reward
self.top_decision_maker.previous_state = self.top_decision_maker.current_state
self.top_decision_maker.previous_action = controller_number
return controller_number
def train_action(self, obs):
self.controller.current_state = handcraft_function.get_all_observation(obs)
if self.controller.previous_action is not None:
self.controller.network.perceive(self.controller.previous_state,
self.controller.previous_action,
self.controller.previous_reward,
self.controller.current_state,
obs.last())
action_and_parameter = self.controller.network.egreedy_action(self.controller.current_state)
self.controller.previous_reward = obs.reward
self.controller.previous_state = self.controller.current_state
self.controller.previous_action = action_and_parameter
action_and_parameter = handcraft_function.reflect(obs, action_and_parameter)
action = handcraft_function.assembly_action(obs, self.index, action_and_parameter)
return action
def train_action(self, obs):
# self.controller.current_state = get_raw_units_observation(obs)
self.controller.current_state = handcraft_function.get_all_observation(
obs)
if self.controller.previous_action is not None:
self.controller.network.perceive(self.controller.previous_state,
self.controller.previous_action,
self.controller.previous_reward,
self.controller.current_state,
obs.last())
# print(obs.reward)
action_and_parameter = self.controller.network.egreedy_action(
self.controller.current_state)
self.controller.previous_reward = reward_compute_1(obs)
self.controller.previous_state = self.controller.current_state
action_and_parameter = handcraft_function.reflect(
len(sa.attack_controller), action_and_parameter)
self.controller.previous_action = action_and_parameter
action = handcraft_function.assembly_action(obs, self.index,
action_and_parameter)
return action
def test_action(self, obs):
self.top_decision_maker.current_state = handcraft_function.get_all_observation(
obs)
return self.top_decision_maker.network.action(
self.top_decision_maker.current_state)
