Rogue-Gym: A New Challenge for Generalization in Reinforcement Learning

Understand

In this paper, we propose Rogue-Gym, a simple and classic style roguelike game built for evaluating generalization in reinforcement learning (RL).

• Combined with the recent progress of deep neural networks, RL has successfully trained human-level agents without human knowledge in many games such as those for Atari 2600.
• However, it has been pointed out that agents trained with RL methods often overfit the training environment, and they work poorly in slightly different environments.
• To investigate this problem, some research environments with procedural content generation have been proposed.