// Agentic World Modeling // Massive 40-author survey just dropped. Cleanest taxonomy of world models in agent research I've seen. (bookmark…

// Agentic World Modeling // Massive 40-author survey just dropped. Cleanest taxonomy of world models in agent research I've seen. (bookmark it) The paper proposes a "levels × laws" framework. Three capability levels: > L1 Predictors do one-step transitions > L2 Simulators do multi-step action-conditioned rollouts > L3 Evolvers self-revise as the world changes It discusses four law regimes, including physical, digital, social, scientific. They synthesize 400+ works and 100+ representative systems spanning model-based RL, video generation, web/GUI agents, multi-agent simulation, and scientific discovery. The framework also identifies failure modes and proposes evaluation principles for each level. Why it matters: as agents shift from chatbots to goal-accomplishers, the bottleneck moves from language to environment. This is the first paper that gives builders a shared vocabulary for designing and evaluating world models across communities that have been working in isolation. Paper: https://arxiv.org/abs/2604.22748 Learn to build effective AI agents in our academy: https://academy.dair.ai/

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Source: DAIR.AI (X) | 2026-04-27