Critiques of World Models
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.
686e8b27d938c25d684419f7
Eric Xing
686e8b27d938c25d684419f8
Mingkai Deng
claimed_verified
2025-07-10T07:09:58.619Z
61718f1eec6894b48c23eec9
/avatars/9f426e0f1ca734fb428a22881d2e7b20.svg
Mingkai Deng
user
mingkaid
686e8b27d938c25d684419f9
Jinyu Hou
claimed_verified
2025-07-10T07:09:55.508Z
6510902581204fcae4215ff8
/avatars/b720e968a7d70ca62d8082b4316838af.svg
Jinyu Hou
user
jinyuhou
686e8b27d938c25d684419fa
Zhiting Hu
Critiques of World Models
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.
A new architecture for a general-purpose world model is proposed, based on hierarchical, multi-level, and mixed continuous/discrete representations, with a focus on simulating actionable possibilities for purposeful reasoning and acting.
world model hierarchical multi-level mixed continuous/discrete representations generative learning self-supervision Physical Agentic and Nested (PAN) AGI system