Complexity Thoughts: Issue #10
Unraveling complexity: building knowledge, one paper at a time
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Networks and Complex Systems Foundations
Generalized network density matrices for analysis of multiscale functional diversity
Statistical physics of information dynamics has been used to define network states in terms of density matrices encoding the interplay between structure and (diffusive-only) dynamics. In this new work, this paradigm has been extended to more general nonlinear (and non-diffusive) dynamics, showing that functional diversity in a complex system is a genuine emergent property which cannot be deduced from the knowledge of topological features such as heterogeneity, modularity, the presence of asymmetries, and dynamical properties of a system.
Emergent stability in complex network dynamics
In a seminal paper in the ‘70s, Robert May has shown under which conditions a large (while random) network is unstable. In this new work, Meena et al show why real-world large complex networks are indeed stable.
Environmental Path-Entropy and Collective Motion
Do you know swarming or flocking of animal systems? Here, the authors show that individual trajectories of agents in a 2D space derive from a “bottom-up” principle: individuals reorient to maximize their future path entropy over environmental states. This can be seen as a proxy for keeping options open, a principle that may confer evolutionary fitness in an uncertain world.
Flocking without Alignment Interactions in Attractive Active Brownian Particles
Flocking with nonaligning attractive interactions? Yes, it’s possible!
Population dynamics
Social copying drives a tipping point for nonlinear population collapse
Stochastic perturbations may trigger a tipping point by runaway dispersal, driving populations to a state of quasi-extinction. The authors fit a dynamical models to population fluctuations over 40 y in a social bird that showed an unexpected collapse after a perturbation press that progressively eroded environmental conditions at the world’s most suitable breeding patch.
Origin of life
Metal-rich stars are less suitable for the evolution of life on their planets
Paradoxically, although metal-rich stars emit substantially less ultraviolet radiation than metal-poor stars, the surface of their planets is exposed to more intense ultraviolet radiation. For the stellar types considered, metallicity has a larger impact on the evolution of life than stellar temperature. During the evolution of the universe, newly formed stars have progressively become more metal-rich, exposing organisms to increasingly intense ultraviolet radiation. The findings by Shapiro et al imply that planets hosted by stars with low metallicity are the best targets to search for complex life on land.
Artificial Intelligence
The current discussion around ChatGPT and its nature has triggered the attention of many complexity scientists and philosophers. I think that the following two papers provide a fair contribution to the ongoing discussion.
This paper argues that because much of meaning is embedded in common patterns of language use, LLMs can model the statistical contours of these usage patterns. The authors agree with distributional semantics that the statistical relations of a text corpus reflect meaning, but only part of it.
The debate over understanding in AI’s large language models
“We survey a current, heated debate in the artificial intelligence (AI) research community on whether large pretrained language models can be said to understand language—and the physical and social situations language encodes—in any humanlike sense. We describe arguments that have been made for and against such understanding and key questions for the broader sciences of intelligence that have arisen in light of these arguments. We contend that an extended science of intelligence can be developed that will provide insight into distinct modes of understanding, their strengths and limitations, and the challenge of integrating diverse forms of cognition”
Book of the week
Conflicting Models for the Origin of Life
Editor(s): Stoyan K. Smoukov, Joseph Seckbach, Richard Gordon
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