A Definition and Roadmap for World Models
- URL: http://arxiv.org/abs/2607.06401v1
- Date: Tue, 07 Jul 2026 15:31:32 GMT
- Title: A Definition and Roadmap for World Models
- Abstract summary: "World models" are internal simulators that learn the structure and dynamics of an environment.<n>There is no consensus on what a world model fundamentally is, what it should predict, or how it should be built.<n>This article provides a scientific definition of world models, discussions of their key technical aspects, and a staged roadmap for developing effective world models.
- Score: 79.8341750557487
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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.
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