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Message definition (Diffusion Models Are Real-Time Game Engines ) '''Future Work.''' We demonstrate ''GameNGen'' on the classic game DOOM. It would be interesting to test it on other games or more generally on other interactive software systems. We note that nothing in our technique is DOOM specific except for the reward function for the RL-agent. We plan on addressing that in future work. While ''GameNGen'' manages to maintain game state accurately, it isn’t perfect, as per the discussion above. A more sophisticated architecture might be needed to mitigate these issues. ''GameNGen'' currently has a limited capability to leverage more than a minimal amount of memory. Experimenting with further expanding the memory effectively could be critical for more complex games/software. ''GameNGen'' runs at 20 or 50 FPS<sup>2</sup><sup>2</sup>Faster than the original game DOOM ran on some of the authors’ 80386 machines at the time! on a TPUv5. It would be interesting to experiment with further optimization techniques to get it to run at higher frame rates and on consumer hardware.
未来工作 我们在经典游戏《DOOM》上演示了GameNGen 。在其他游戏或更广泛的交互式软件系统上进行测试会非常有趣。我们注意到，除了强化学习代理的奖励函数外，我们的技术没有任何内容是《DOOM》特有的。我们计划在未来的工作中解决这个问题。虽然GameNGen 能够准确地维护游戏状态，但如上文所述，它并不完美。可能需要一个更复杂的架构来缓解这些问题。GameNGen 目前只能利用有限的内存。尝试进一步有效地扩展内存对于更复杂的游戏或软件来说至关重要。GameNGen 在TPUv5上的运行速度为20或50 FPS，比原始游戏《DOOM》当时在一些作者的80386机器上的运行速度还要快！在消费者硬件上尝试进一步的优化技术以提高帧率将是很有趣的。
