Critiques of World Models
Authors: name: Eric Xing, name: Mingkai Deng, name: Jinyu Hou, name: Zhiting Hu

World Model, the supposed algorithmic surrogate of the real-world environment
which biological agents experience with and act upon, has been an emerging
topic in recent years because of the rising needs to develop virtual agents
with artificial (general) intelligence. There has been much debate on what a
world model really is, how to build it, how to use it, and how to evaluate it.
In this essay, starting from the imagination in the famed Sci-Fi classic Dune,
and drawing inspiration from the concept of "hypothetical thinking" in
psychology literature, we offer critiques of several schools of thoughts on
world modeling, and argue the primary goal of a world model to be simulating
all actionable possibilities of the real world for purposeful reasoning and
acting. Building on the critiques, we propose a new architecture for a
general-purpose world model, based on hierarchical, multi-level, and mixed
continuous/discrete representations, and a generative and self-supervision
learning framework, with an outlook of a Physical, Agentic, and Nested (PAN)
AGI system enabled by such a model.