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A new model for evolving Evolutionary Algorithms is proposed in this paper. The model is based on the Linear Genetic Programming (LGP) technique. Every LGP chromosome encodes an EA which is used for solving a particular problem. Several…

Neural and Evolutionary Computing · Computer Science 2021-09-28 Mihai Oltean

Development combines three basic processes asymmetric --- cell division, signaling and gene regulation --- in a multitude of ways to create an overwhelming diversity of multicellular life-forms. Here, we attempt to chart this diversity…

Molecular Networks · Quantitative Biology 2020-01-01 Somya Mani , Tsvi Tlusty

The forest of mutations associated to a multitype branching forest is obtained by merging together all vertices of its clusters and by preserving connections between them. We first show that the forest of mutations of any mulitype branching…

Probability · Mathematics 2015-10-06 Loïc Chaumont , Thi Ngoc Anh Nguyen

Infinite population models are important tools for studying population dynamics of evolutionary algorithms. They describe how the distributions of populations change between consecutive generations. In general, infinite population models…

Neural and Evolutionary Computing · Computer Science 2015-09-29 Bo Song , Victor O. K. Li

Consider a population that is expanding in two-dimensional space. Suppose we collect data from a sample of individuals taken at random either from the entire population, or from near the outer boundary of the population. A quantity of…

Probability · Mathematics 2026-03-16 Shirshendu Ganguly , Jason Schweinsberg , Yubo Shuai

Learning ensembles by bagging can substantially improve the generalization performance of low-bias, high-variance estimators, including those evolved by Genetic Programming (GP). To be efficient, modern GP algorithms for evolving (bagging)…

Neural and Evolutionary Computing · Computer Science 2021-02-08 Marco Virgolin

Rapid advance of experimental techniques provides an unprecedented in-depth view into complex developmental processes. Still, little is known on how the complexity of multicellular organisms evolved by elaborating developmental programs and…

Molecular Networks · Quantitative Biology 2021-07-16 Somya Mani , Tsvi Tlusty

Phylogenetic trees are simple models of evolutionary processes. They describe conditionally independent divergent evolution of taxa from common ancestors. Phylogenetic trees commonly do not have enough flexibility to adequately model all…

Populations and Evolution · Quantitative Biology 2025-11-11 Jonathan D. Mitchell , Barbara R. Holland

The properties of randomly evolving special trees having defined and analyzed already in two earlier papers (arXiv:cond-mat/0205650 and arXiv:cond-mat/0211092) have been investigated in the case when the continuous time parameter converges…

Statistical Mechanics · Physics 2007-05-23 L. Pal

Finding the optimal parameter setting (i.e. the optimal population size, the optimal mutation probability, the optimal evolutionary model etc) for an Evolutionary Algorithm (EA) is a difficult task. Instead of evolving only the parameters…

Neural and Evolutionary Computing · Computer Science 2021-09-29 Mihai Oltean , Crina Groşan

We consider the hypothesis that Evolution promotes population-wide genome patterns that, under randomization, ensures the External Validity of adaptations across population members. An adaptation is Externally Valid (EV) if its effect holds…

Populations and Evolution · Quantitative Biology 2021-08-17 Andre F. Ribeiro

Lateral gene transfer (LGT) is a common mechanism of non-vertical evolution where genetic material is transferred between two more or less distantly related organisms. It is particularly common in bacteria where it contributes to adaptive…

Probability · Mathematics 2012-06-18 Sebastien Roch , Sagi Snir

We present a model for growth in a multi-species population. We consider two types evolving as a logistic branching process with mutation, where one of the types has a selective advantage, and are interested in the regime in which the…

Probability · Mathematics 2025-07-18 Marta Dai Pra , Julian Kern

Large Language Models (LLMs) have demonstrated great promise in generating code, especially when used inside an evolutionary computation framework to iteratively optimize the generated algorithms. However, in some cases they fail to…

Neural and Evolutionary Computing · Computer Science 2025-03-24 Niki van Stein , Anna V. Kononova , Lars Kotthoff , Thomas Bäck

Many life-history traits, like the age at maturity or adult longevity, are important determinants of the generation time. For instance, semelparous species whose adults reproduce once and die have shorter generation times than iteroparous…

Populations and Evolution · Quantitative Biology 2016-04-22 Mélissa Verin , Salomé Bourg , Frédéric Menu , Etienne Rajon

We consider the evolution of large but finite populations on arbitrary fitness landscapes. We describe the evolutionary process by a Markov, Moran process. We show that to $\mathcal O(1/N)$, the time-averaged fitness is lower for the finite…

Populations and Evolution · Quantitative Biology 2015-06-04 Dirk M. Lorenz , Jeong-Man Park , Michael W. Deem

The ongoing explosion of genome sequence data is transforming how we reconstruct and understand the histories of biological systems. Across biological scales, from individual cells to populations and species, trees-based models provide a…

Populations and Evolution · Quantitative Biology 2025-12-08 Yun Deng , Shing H. Zhan , Yulin Zhang , Chao Zhang , Bingjie Chen

We consider a neutral haploid population whose generations are not overlapping and whose size is large and constantly of $N$ individuals. Any generation is replaced by a new one and any individual has a single parent. We do not choose the…

Populations and Evolution · Quantitative Biology 2009-11-11 Maurizio Serva

The time process of transport on randomly evolving trees is investigated. By introducing the notions of living and dead nodes a model of random tree evolution is constructed which describes the spreading in time of objects corresponding to…

Statistical Mechanics · Physics 2009-11-11 L. Pal

Several genetic programming systems are created, each solving a different problem. In these systems, the median number of generations G needed to evolve a working program is measured. The behavior of G is observed as the difficulty of the…

Neural and Evolutionary Computing · Computer Science 2011-02-15 Mike Stimpson