这篇给了世界模型的具体定义和路线图，适合想了解它在强化学习、视频生成、机器人等领域不同玩法的人。
一篇视角文章提出了世界模型的科学定义和分阶段路线图，涵盖从基于模型的强化学习、视频生成到具身机器人和物理AI等子领域。文章指出当前对世界模型缺乏共识，并讨论了关键技术方面，包括预测内容与构建方法。它为不同研究方向的世界模型开发提供了系统性框架。
A Definition and Roadmap for World Models
World models -- internal simulators that learn the structure and dynamics of an environment -- have become one of the most actively debated concepts in AI. From model-based reinforcement learning and video generation to embodied robotics and ultimately, physical AI, researchers across AI subfields are building systems that they call "world models", yet there is no consensus on what a world model fundamentally is, what it should predict, or how it should be built. This perspective article provides a scientific definition of world models, discussions of their key technical aspects, and a staged roadmap for developing effective world models.