Setting aside the choice of LLM, the constraint that the LLM must maintain a world-model-as-knowledge-graph solely by reading and re-reading its own chat history seems to be a less interesting experiment than providing it with tools that let it develop that world model explicitly?

On page 5, Figure 1, the authors create a hand-written diagram showing the relationship between objects as a graph showing the directionality of edges in 3D space. To me, this implies that you could supply your LLM with a set of tools like getObjectsInGraph, updateGraphRelatingObjectPair, findObjectsRelativeToObject, describePathBetweenObjectsByName... and allow it to maintain that diagram as a structured DAG, and continually ask the game engine questions that let it update that graph in an agentic way. My prediction would be that they'd recreate that diagram, and enable goal seeking, with high fidelity.

Asking an LLM to work without being able to "visualize" and "touch" its environment in its "mind's eye" is tying a hand behind its back. But I'm bullish that we'll find increasingly better ways of adapting 3D/4D world models into textual tools in a way that rapidly changes the possibilities of what LLMs can do.