SOURCE-LINKED INTELLIGENCE
World-Action Models for Robot Learning and Control: A Survey
Robots operating in open environments act under partial observability, physical constraints, and dynamic task contexts. Beyond mapping observations and language instructions to actions, they must anticipate how candidate actions may affect future states and task-relevant outcomes. Recent advances in world models, video generation, and Vision-Language-Action (VLA) policies have motivated the development of World-Action Models (WAMs), which couple future world prediction with executable action generation. This survey provides a robotics-oriented review of WAMs. We clarify their scope relative to
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-13T16:35:56.000Z
First collected: 2026-09-20T12:21:05.240Z. This is not the publication date.