Nature Machine Intelligence, Published online: 18 September 2026; doi:10.1038/s42256-026-01312-x Living organisms continuously monitor their internal physiological states while interacting with complex environments and adapt their actions in response to changes in these internal signals. New work combines such biological principles with cybernetics, reinforcement learning and neuroscience to devel

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ResearcherLee et al. propose modeling internal states as stable contextual variables that tune policy selection, exploration and memory, not just as reward signals.

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