def __init__(self, env, config=None):
super(AbstractDQNAgent, self).__init__(config)
self.env = env
assert isinstance(env.action_space, spaces.Discrete) or isinstance(env.action_space, spaces.Tuple), \
"Only compatible with Discrete action spaces."
self.memory = ReplayMemory(self.config)
self.exploration_policy = exploration_factory(self.config["exploration"], self.env.action_space)
self.training = True
self.previous_state = None
def __init__(self, env, config=None):
super(AbstractDQNAgent, self).__init__(config)
self.env = env
assert isinstance(
env.action_space,
spaces.Discrete), "Only compatible with Discrete action spaces."
self.config["model"]["in"] = int(np.prod(env.observation_space.shape))
self.config["model"]["out"] = env.action_space.n
self.memory = ReplayMemory(self.config)
self.exploration_policy = exploration_factory(
self.config["exploration"], self.env.action_space)
self.training = True
self.previous_state = None
def eval(self):
self.training = False
self.config['exploration']['method'] = "Greedy"
self.exploration_policy = exploration_factory(
self.config["exploration"], self.env.action_space)