def __init__(self, env: GameWrapperEnvironment, weight_file=None):
"""Build a simple DQN model"""
BaseAgent.__init__(self, env)
nb_actions: int = flatdim(env.action_space)
model = Sequential()
model.add(Flatten(input_shape=(1, flatdim(env.observation_space))))
model.add(Dense(16))
model.add(Activation("relu"))
model.add(Dense(16))
model.add(Activation("relu"))
model.add(Dense(16))
model.add(Activation("relu"))
model.add(Dense(nb_actions))
model.add(Activation("linear"))
print(model.summary())
# Finally, we configure and compile our agent. You can use every built-in Keras optimizer and
# even the metrics!
memory = SequentialMemory(limit=50000, window_length=1)
policy = BoltzmannQPolicy()
DQNAgent.__init__(
self,
model=model,
nb_actions=nb_actions,
memory=memory,
nb_steps_warmup=10,
target_model_update=1e-2,
policy=policy,
)
# Ensure we compile an optimizer for target model
self.compile(Adam(lr=1e-3), metrics=["mae"])
if weight_file is not None:
self.load_weights(weight_file)
