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cs.AI2026
From monoliths to modules: Decomposing transducers for efficient world modelling
Alexander Boyd, Franz Nowak, David Hyland +2
World models have been recently proposed as sandbox environments in which AI agents can be trained and evaluated before deployment. While realistic world models often have high com…
cs.AI2025
AI in a vat: Fundamental limits of efficient world modelling for agent sandboxing and interpretability
Fernando Rosas, Alexander Boyd, Manuel Baltieri
Recent work proposes using world models to generate controlled virtual environments in which AI agents can be tested before deployment to ensure their reliability and safety. Howev…
cs.AI2024
Disentangled Representations for Causal Cognition
Filippo Torresan, Manuel Baltieri
Complex adaptive agents consistently achieve their goals by solving problems that seem to require an understanding of causal information, information pertaining to the causal relat…