iFuture is a premier open-access journal published by Tsinghua University Press on the SciOpen platform, with academic support from the Institute for Interdisciplinary Information Sciences at Tsinghua University. Led by Turing Award Laureate Prof. Andrew Chi-Chih Yao as Editor-in-Chief, the journal is the core component of the AI Open Alliance. Its core mission is to break through AI’s theoretical bottlenecks and foundational infrastructure.
Yang Yuan、Andrew Chi-Chih Yao
In this paper, we propose “Calculus of Intelligence” (COIN), a mathematical framework that formalizes agentic tasks as typed free-monadic task spaces inside a Grothendieck topos, and studies them as a calculus: differentiation via task-space decomposition, differentials as the resulting local task spaces, and integration via monadic composition together with sheaf-theoretic compatibility of declared overlaps. COIN treats a task as a valid-plan space rather than as a single output: the user intent is progressively elaborated into a typed task space, and each valid decomposition presents a sound subspace of plans obtainable from local solutions whose declared overlaps agree and whose composition is certified.
2026-07-17
iFuture is a premier open-access journal published by Tsinghua University Press on the SciOpen platform, with academic support from the Institute for Interdisciplinary Information Sciences at Tsinghua University. Led by Turing Award Laureate Prof. Andrew Chi-Chih Yao as Editor-in-Chief, the journal is the core component of the AI Open Alliance. Its core mission is to break through AI’s theoretical bottlenecks and foundational infrastructure.
Yang Yuan、Andrew Chi-Chih Yao
In this paper, we propose “Calculus of Intelligence” (COIN), a mathematical framework that formalizes agentic tasks as typed free-monadic task spaces inside a Grothendieck topos, and studies them as a calculus: differentiation via task-space decomposition, differentials as the resulting local task spaces, and integration via monadic composition together with sheaf-theoretic compatibility of declared overlaps. COIN treats a task as a valid-plan space rather than as a single output: the user intent is progressively elaborated into a typed task space, and each valid decomposition presents a sound subspace of plans obtainable from local solutions whose declared overlaps agree and whose composition is certified.
2026-07-17