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cs.AI2026
Hierarchical Behaviour Spaces
Michael Tryfan Matthews, Anssi Kanervisto, Jakob Foerster +3
Recent work in hierarchical reinforcement learning has shown success in scaling to billions of timesteps when learning over a set of predefined option reward functions. We show tha…
cs.AI2025
DigiData: Training and Evaluating General-Purpose Mobile Control Agents
Yuxuan Sun, Manchen Wang, Shengyi Qian +18
AI agents capable of controlling user interfaces have the potential to transform human interaction with digital devices. To accelerate this transformation, two fundamental building…
cs.AI2024
MaestroMotif: Skill Design from Artificial Intelligence Feedback
Martin Klissarov, Mikael Henaff, Roberta Raileanu +7
Describing skills in natural language has the potential to provide an accessible way to inject human knowledge about decision-making into an AI system. We present MaestroMotif, a m…