Discover Artificial Intelligence
A survey of world models for physical AI with uncertainty representation and control
Abstract Physical AI systems must reason about real-world dynamics in order to perceive, predict, and act safely under partial observability and uncertainty. World models–learned predictive representations of environment dynamics and action consequences–have emerged as a unifying framework for integrating perception, prediction, planning, and control in embodied agents. This survey provides a comprehensive and technically grounded review of learning-based world models for Physical AI, with particular emphasis on cl …