Thomas F. Varley, Josh Bongard
The study of complex systems has produced a huge library of different descriptive statistics that scientists can use to describe the various emergent patterns that characterize complex systems. The problem of engineering systems to display those patterns from first principles is a much harder one, however, as a hallmark of complexity is that macro-scale emergent properties are often difficult to predict from micro-scale features. Here, we propose a general optimization-based pipeline to automate the difficult problem of engineering emergent features by re-purposing descriptive statistics as loss functions, and letting a gradient descent optimizer do the hard work of designing the relevant micro-scale features and interactions. Using Kuramoto systems of coupled oscillators as a test bed, we show that our approach can reliably produce systems with non-trivial global properties, including higher-order synergistic information, multi-attractor metastability, and meso-scale structures such as modules and integrated information. We further show that this pipeline can also account for and accommodate constraints on the system properties, such as the costs of connections, or topological restrictions. This work is a step forward on the path moving complex systems science from a field predicated largely on description and post-hoc storytelling towards one capable of engineering real-world systems with desirable emergent meso-scale and macro-scale properties.

Read the full article at: arxiv.org

Jonas Wickman, Christopher A. Klausmeier, and Elena Litchman

The American Naturalist

Environmental variability, in the form of either temporal fluctuations or intermittent perturbations, affects virtually all ecological systems. However, while temporal variability is widely recognized to play an important role across many ecological and evolutionary subdisciplines, there is no high-level cross-cutting concept that describes how species, communities, and ecosystems respond to variability. In this article we propose that “antifragility” could serve well as such a concept. Initially used in economics, antifragility denotes that a property or metric of performance increases with variability. To showcase the breadth of applicability and utility of the concept, we examine two mathematical models for antifragility in ecosystem services and competition. We also demonstrate some of the nuances and possible misapplications of the concept. Under global change, the variability of environmental conditions is expected to change. We believe that antifragility could serve as a useful concept in coordinating research efforts toward understanding the effects of these changes.

Read the full article at: www.journals.uchicago.edu

Vicky Chuqiao Yang, James Holehouse, Hyejin Youn, José Ignacio Arroyo, Sidney Redner, Geoffrey B. West, and Christopher P. Kempes

PNAS 123 (7) e2509729123

Diversification and specialization are central to complex adaptive systems, yet overarching principles across domains remain elusive. We introduce a general theory that unifies diversity and specialization across disparate systems, including microbes, federal agencies, companies, universities, and cities, characterized by two key parameters. We show from extensive data that function diversity scales with system size as a sublinear power law-resembling Heaps’ law-in all but cities, where it is logarithmic. Our theory explains both behaviors and suggests that function creation depends on system goals and structure: federal agencies tend to ensure functional coverage; cities slow new function growth as old ones expand, and cells occupy an intermediate position. Once functions are introduced, their growth follows a remarkably universal pattern across all systems.

Read the full article at: www.pnas.org