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cs.AI2026
Toward a Science of Intent: Closure Gaps and Delegation Envelopes for Open-World AI Agents
Maximiliano Armesto, Christophe Kolb
Recent work has framed intelligence in verifiable tasks as reducing time-to-solution through learned structure and test-time search, while systems work has explored learned runtime…
cs.AI2026
Coupled Control, Structured Memory, and Verifiable Action in Agentic AI (SCRAT -- Stochastic Control with Retrieval and Auditable Trajectories): A Comparative Perspective from Squirrel Locomotion and Scatter-Hoarding
Maximiliano Armesto, Christophe Kolb
Agentic AI is increasingly judged not by fluent output alone but by whether it can act, remember, and verify under partial observability, delay, and strategic observation. Existing…