PAN: A World Model for General, Actionable, and Long-Horizon World Simulation

Understand

A world model is a cognitive simulator of the real-world environment allowing biological agents to reason about how the world evolves, whether spontaneously or in response to their actions, and accordingly to plan and strategize.

• In building Artificial Intelligence (AI) systems, world models represent the next frontier beyond large language models (LLMs) to enable physical and embodied intelligence in AI agents, allowing them to perform decision-making through simulative reasoning and reinforcement-learning through simulative trials.
• Recent advancements in world modeling have yielded impressive progress in video generation, 3-D scene evolution, robotic dynamics, and game simulation, but limitations persist in general, open-domain, action-driven prediction, long-horizon consistency, and abstract reasoning and planning.
• Moreover, fundamental architectural questions, whether it be state representation, information flow, or training objectives, remain unresolved.