7/12/2026 at 7:48:43 PM
Ha, interesting. I wasn't aware of Sutton's blog post, but if I might make a shameless plug, we demonstrated [1] exactly this problem (see section 4.4.3), and how multi-step world models (using diffusion models as the substrate) could be one potential answer.Since then, I have come to like temporally-abstract models more and more. Rolling out in time -- either step-by-step or many steps at once -- suffers from the tyranny of the specific. For long horizon planning with agents, I care (often only approximately) about where I can end up, and seldom about exactly when I end up there. Successor features, GVFs, Forward-Backward representations, and the like seem like they have an elegant approach for structuring thinking at a "high level", instead of generating exponentially large search trees by rolling out microscopic world models.
[1] https://arxiv.org/abs/2410.05364 (funnily, from around the same time / few months after Sutton's blog post)
by ssivark
7/12/2026 at 9:39:02 PM
What do you mean by tyranny of the specific?by sawyers
7/13/2026 at 3:10:41 AM
Imagine I want to attend a conference in a different country. Google maps might give turn by turn navigation but that is an overwhelming and largely irrelevant mess of details for most planning purposes. Eg: all I might want to know is the different flight legs and the fact that the journey takes 15-18 hours, and not all the turns and traffic lights to get from home to the airport.I want a zoomed out picture, and to be able to fill in detail hierarchically, on demand. Instead, one-step models give you the full high-res local structure of the graph that would have to search through (with too many states and edges).
by ssivark