Before revision: In some puzzles, the strategy we need to use near the goal can be quite different from the strategy that is effective earlier on , e.g. due to a smaller branching factor near the exit state in a maze.
After revision: Despite seminal advances in reinforcement learning in recent years, many domains where the rewards are sparse , e.g. due to a smaller branching factor near the exit state in a maze.