I am sure the classic (linear) Q-learning algorithm can solve Lunar Lander when the state space is discretized using tile coding.

Are you saying you solved it using tabular Q-learning, that is, by learning about each discretized state independently? I would be curious to know what kind of discretization you used and how many training steps were required.