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cs.AI2025
ExoPredicator: Learning Abstract Models of Dynamic Worlds for Robot Planning
Yichao Liang, Dat Nguyen, Cambridge Yang +7
Long-horizon embodied planning is challenging because the world does not only change through an agent's actions: exogenous processes (e.g., water heating, dominoes cascading) unfol…
cs.RO2025★ 1 cited
From Pixels to Predicates: Learning Symbolic World Models via Pretrained Vision-Language Models
Ashay Athalye, Nishanth Kumar, Tom Silver +4
Our aim is to learn to solve long-horizon decision-making problems in complex robotics domains given low-level skills and a handful of short-horizon demonstrations containing seque…