S-AI-Recursive: Bio-Inspired Sparse AI Architecture for Iterative Reasoning

A recent publication on arXiv presents S-AI-Recursive, a bio-inspired architecture for Sparse Artificial Intelligence that treats reasoning as a hormonal closed-loop iteration instead of a straightforward feed-forward process. This research builds upon the foundational S-AI framework, the hormonal-probabilistic unification doctrine, and the S-AI-IoT methodology. It defines the Recursive Reasoning Cycle (RRC) as a dynamic system influenced by two innovative hormones: Clarifine, which acts as a convergence signal, and Confusionin, an uncertainty detector. Their opposing regulation facilitates iterative refinement of states toward a stable cognitive equilibrium. The comprehensive mathematical framework encompasses recursive state dynamics, a Lyapunov stability proof, an entropic contraction theorem, a hormonal stopping criterion with a finite-time termination guarantee, and Euler-Maruyama discretization with projection. The paper is available as arXiv:2605.13872.