Researchers have introduced a new AI architecture called S-AI-Recursive, which uses a bio-inspired approach to implement reasoning as a closed-loop iteration. This is achieved through the interaction of two hormones, Clarifine and Confusionin, that regulate state refinement, stopping, resource allocation, and recursive-engram retrieval. The framework includes various techniques such as Lyapunov analysis and multi-signal stopping to optimize performance. Experimental results show that S-AI-Recursive can reduce iteration depth by 43.4% on convergent Maze instances and accelerate task completion on recurring Sudoku instances. --- Why it matters: This work matters because it presents a novel approach to recursive reasoning, which is essential for tasks involving complex decision-making and problem-solving. The ability to adaptively stop and allocate resources could lead to more efficient AI systems that can handle challenging tasks more effectively. Source: https://arxiv.org/abs/2605.13872