Montezumas Revenge

Montezuma's Revenge is a well-known ATARI 2600 benchmark game, distinguished by its high difficulty for reinforcement learning algorithms. The objective of the task is to design algorithms that can effectively encourage environmental exploration to achieve efficient navigation and puzzle-solving within the game. This research has significant application value in improving the performance of reinforcement learning in complex environments.