Agentic World Modeling: Survey Identifies Environment Dynamics as Central Bottleneck for Goal-Directed AI

arXiv·medium signal

Comprehensive survey argues that as AI systems move from text generation to sustained goal-directed interaction, the ability to model environment dynamics becomes the central bottleneck. Covers agents that manipulate objects, navigate software, coordinate with others, and design experiments, establishing foundations for understanding what world models agents need to act effectively in complex environments.