Punctuated Equilibrium Seems to be the Way of Things

Here's a short article about punctuated equilibrium in biological systems, proteins, and (surprise!) languages at Quanta.

I was very surprised to see PE arising in some genetic algorithm work I was doing several decades ago on systems that were entirely non-biological.  I simply remarked on it in the resulting paper and moved on with the main thrust of that research.  Still, the waves of evolution in this system did show significant regularity and could be useful in determining when some point of diminishing return has been reached, and hence when to stop burning computer cycles.

Looking around on the web using an AI search quickly showed that this has been observed many times before:

Give me a list of research showing punctuated equilibrium in genetic algorithm simulations of non-biological systems.

Here is a list of relevant research papers that demonstrate or analyze punctuated equilibrium (periods of stasis followed by rapid changes) in genetic algorithm (GA) simulations applied to non-biological systems, such as abstract optimization problems, engineering tasks, or artificial life models. I've focused on studies where the systems are clearly non-biological (e.g., not direct simulations of real biological processes like speciation or genetic drift in organisms). Each entry includes the title, authors, year, a brief description of the GA and system, and how punctuated equilibrium is shown. The list is chronological.

• Punctuated Equilibria in Genetic Search by Michael D. Vose and Gunar E. Liepins (1991). This paper formalizes a simple GA with selection, mutation, and one-point crossover, applied to non-biological search spaces modeled as high-dimensional dynamical systems. Simulations and mathematical analysis show punctuated equilibrium through alternating periods of relative stability (attractors) and sudden rapid evolution when populations shift between basins, supported by eigenvalue computations and trajectory diagrams.
• Genetic Algorithms and Punctuated Equilibria in VLSI by J. P. Cohoon, W. N. Martin, and D. S. Richards (1991). A distributed GA with subpopulation structures is used for the K-partition problem in VLSI (Very Large Scale Integration) chip design, a non-biological engineering optimization task. The approach is inspired by punctuated equilibrium theory, with empirical simulations demonstrating performance advantages from "ecological opportunities" that enable rapid evolutionary bursts after periods of stasis.
• Population-Based Incremental Learning: A Study on Genetic Algorithms and Simulated Annealing by Shumeet Baluja (1994). This work uses Population-Based Incremental Learning (an extension of equilibrium GAs) compared to standard GAs on non-biological optimization problems like numerical functions (e.g., De Jong’s, Griewangk’s), NP-complete tasks (e.g., jobshop scheduling, traveling salesman), and deceptive problems. It demonstrates punctuated equilibrium in parallel GA variants with subpopulations, where stasis in isolated groups is interrupted by migrations leading to rapid improvements, shown via a contrived example where single-population GAs fail but multi-population ones succeed.
• Punctuated Equilibria in Simple Genetic Algorithms for Functions of Unitation by Sangyeop Oh and Hyunsoo Yoon (2000). A simple GA with roulette wheel selection, mutation, and crossover is simulated on non-biological unitation functions (bit-string optimization in bistable potential landscapes). Theoretical analysis via diffusion equations and simulations reveal punctuated equilibrium, with long metastable periods at local optima followed by exponential-duration sudden jumps to global optima, visualized in population mean trajectories and parameter-dependent duration plots.
• Punctuation Equilibrium and Optimization: An A-Life Model by Ravi Jonnal and Anthony Chemero (2000). An evolutionary algorithm evolves artificial neural network weights for controlling a virtual creature in a 2D grid-based simulated environment with resources and obstacles (non-biological artificial life setup). Simulations compare standard and punctuated mutation rates, showing that introducing rare bursts of higher mutation leads to punctuated equilibrium patterns—long stasis interrupted by rapid fitness gains—resulting in significantly higher overall fitness scores.
• Punctuated Equilibrium and Neutral Networks in Genetic Algorithms by David Shorten and Geoff Nitschke (2022). A simple GA is applied to non-biological benchmark optimization functions (11 numerical ones plus Royal Road and Trap functions). Empirical simulations demonstrate punctuated equilibrium as populations explore neutral networks (genotype spaces with stable phenotypes), leading to periods of phenotypic stasis followed by rapid changes when escaping to fitter regions, analyzed via consensus sequences and genotype-phenotype

Huh.  Effect noted, explained, harnessed.  I wish search engines had been this effective in 2007.  Back to and onward with my real work.