Reinforcement Learning Algorithms with Python

Landing a spacecraft using REINFORCE

The algorithm is complete however, the most interesting part has yet to be explained. In this section, we'll apply REINFORCE to LunarLander-v2, an episodic Gym environment with the aim of landing a lunar lander.

The following is a screenshot of the game in its initial position, and a hypothetical successful final position:

This is a discrete problem, and the lander has to land at coordinates (0,0), with a penalty if it lands far from that point. The lander has a positive reward when it moves from the top of the screen to the bottom, but when it fires the engine to slow down, it loses 0.3 points on each ...