What question did this study set out to answer?

This study aims to explore the dynamics of biological transitions through a multi-agent framework using a generative operator pipeline.

May 20, 2026Open Access

Biological Transitions as Multi-Agent Realisations of the Generative Operator Pipeline in TO/TOGT

Key Points

This study aims to explore the dynamics of biological transitions through a multi-agent framework using a generative operator pipeline.
Utilized multi-agent simulations to analyze various biological transitions.
Applied mathematical frameworks such as fixed-point theory and contraction mapping in biological contexts.
Conducted experiments examining HPA-axis bifurcation and circadian regulation.
Demonstrated convergence in agent trajectories under the defined generative operator (G).
Identified significant bifurcation events in the HPA-axis and implications for regulatory mechanisms.
Proved 18 mathematical facts related to the operator pipeline without gaps in verification.

Abstract

Biological Transitions as Multi-Agent Realisations of G = U∘F∘K∘C Version 2 — Complete Pablo Nogueira Grossi · May 2026 Concept DOI (all versions): https: //doi. org/10. 5281/zenodo. 19208015Series root: https: //doi. org/10. 5281/zenodo. 19117399GitHub: https: //github. com/TOTOGT/AXLEContact: pgrossi888@outlook. com · g6llc@proton. meORCID: 0009-0000-6496-2186 What this deposit contains File Description multiₐgentₜogtᵥ2. pdf Complete V2 paper (9 pages, 4 figures) multiₐgentₜogt. tex LaTeX source multiₐgentₜogt. py Python simulation the paper applies existing fixed-point, contraction-mapping, and pitchfork results to new domains. License Creative Commons Attribution Non Commercial No Derivatives 4. 0 International (CC BY-NC-ND 4. 0).

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Pablo Nogueira Grossi (Thu,) studied this question.

synapsesocial.com/papers/6a0d50aef03e14405aa9c9ef https://doi.org/https://doi.org/10.5281/zenodo.20230612

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