Stochastic–dissipative least-action framework for self-organizing biological systems, Part I: Variational rationale and Lyapunov-type behavior

How and why do complex chemical and biological systems self-organize into ordered states far from thermodynamic equilibrium? Despite advances in thermodynamics, kinetics, and information theory, a unifying principle that links organization and efficiency across scales has remained elusive. In open systems, productive-event trajectories are conditioned on starting at a source and ending at a sink. This work proposes a stochastic–dissipative least-action triad framework in which (i) a path-ensemble weighting biases trajectories by their action cost, (ii) feedback processes sharpen this distribution, and (iii) the ensemble evolves toward a least-average-action attractor, decreasing during self-organization and increasing during decay. A parametric cross-scale metric—Average Action Efficiency (AAE)—is defined, which is inversely proportional to the average action per productive event. Under reinforcing feedback, identities derived from the exponential-family path measure show that the average action decreases and AAE rises monotonically. In future extensions, this formulation could help bridge quantum, classical, and biological regimes while remaining computationally tractable, because its empirical version relies on aggregate energetic and timing data rather than enumerating individual trajectories. AAE reaches a local maximum at a non-equilibrium steady state under fixed operational context, consistent with the present formulation, and connections to thermodynamic and informational measures are made. A companion article (Part II) details empirical estimation strategies and applications (Georgiev, 2025a).

Georgi Yordanov Georgiev

BioSystems

Volume 262, April 2026, 105647

Read the full article at: www.sciencedirect.com

BeComplex 2026 – Belgrade School on Complex Systems

21-27 June 2026 at Petnica Science Center.

Most of the everyday phenomena we see around us can be categorized as “complex.” Such systems consist of many strongly interacting parts and yet, despite this, they exhibit a certain emergent qualitative unity which endows them with a distinct being, separate, although not independent, from that of their constituent elements.
These complex systems thus possess a kind of “simplicity” as well, which makes them intelligible and allows them to be studied in their own right. The sheer diversity of complex phenomena—from magnets to climate to the economy to the human brain—prevents them from being investigated under a single theoretical framework. Still, studies such as those of Lorenz and Mandelbrot in the 1970s began to reveal a surprisingly large number of common motifs across these systems, including transitions to chaos, fractal structures, pattern formation, and more.
The search for common features of complex systems still remains open. However, most efforts today are focused on understanding particular phenomena. The “Belgrade School of Complex Systems,” organized by the Faculty of Physics at the University of Belgrade (http://www.ff.bg.ac.rs/Engleski/index_eng.html), is an attempt to bring together experts from around the world working on various fields that fall under the broad category of complex systems in order to encourage the exchange of knowledge and promote collaboration between like-minded researchers that may be working in seemingly disparate fields.

More at: becomplex.net

Evolving self-organisation workshop @ GECCO 2026

We are thrilled to be returning to GECCO for a second edition of the Evolving Self-organisation workshop and are now accepting submissions!

Website: https://evolving-self-organisation-workshop.github.io/gecco-2026/

Submission deadline: March 27
Where: GECCO 2026 is a hybrid conference, with its physical venue located in San José, Costa Rica.
When: the conference dates are July 13-17, workshops traditionally happen during the first two days with exact date announced later

The organizing committee
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Alex Mordvintsev (Google Research, Zurich)

Eleni Nisioti (IT University of Copenhagen)
Eyvind Niklasson (Google Research, Zurich)

Ettore Randazzo (Google Research, Zurich)

Mayalen Etcheverry (Google Research, Zurich)

Marcello Barylli (IT University of Copenhagen)
Milton Montero (IT University of Copenhagen)

Sebastian RIsi (IT University of Copenhagen)

Bacterial sensors poised at criticality | Nature Physics

Junhua Yuan
Nature Physics (2026)

Spontaneous switching between active and inactive states in bacterial chemosensory arrays is shown to operate near a critical point. Through biologically controlled disorder, cells balance high signal gain with fast response.

Read the full article at: www.nature.com

Optimizing economic complexity

Viktor Stojkoski, César A. Hidalgo

Research Policy Volume 55, Issue 4, May 2026, 105454

Efforts to apply economic complexity to identify diversification opportunities often rely on diagrams comparing the relatedness and complexity of products, technologies, or industries. Yet, the use of these diagrams, is not based on empirical or theoretical evidence supporting some notion of optimality. Here, we introduce an optimization-based framework that identifies diversification opportunities by minimizing a cost function capturing the constraints imposed by an economy’s pattern of specialization. We show that the resulting portfolios often differ from those implied by relatedness–complexity diagrams, providing a target-oriented optimization layer to the economic complexity toolkit.

Read the full article at: www.sciencedirect.com