Artificial Intelligence, Data Science, Machine Learning, Reinforcement Learning, Programming.
gym env env = gym.make('LunarLander-v2') input_shape = env.observation_space.shape[0] num_actions = env.action_space.n state = env.reset() done = False count=0 done=False steps = 0 #loading trained model policy_network = tf.keras.models.load_model('keras') Now the loop for running the simulation