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The factors that influence genetic architecture shape the structure of the fitness landscape, and therefore play a large role in the evolutionary dynamics. Here the NK model is used to investigate how epistasis and pleiotropy -- key…

种群与进化 · 定量生物学 2013-04-16 Bjørn Østman

These notes introduce probabilistic landscape models defined on high-dimensional discrete sequence spaces. The models are motivated primarily by fitness landscapes in evolutionary biology, but links to statistical physics and computer…

种群与进化 · 定量生物学 2025-12-24 Sakshi Pahujani , Joachim Krug

Evolution in changing environments is an important, but little studied aspect of the theory of evolution. The idea of adaptive walks in fitness landscapes has triggered a vast amount of research and has led to many important insights about…

生物物理 · 物理学 2007-05-23 Claus O. Wilke

Fitness landscapes are mappings between genotypes, phenotypes, and fitness that shape evolution. In recent years, empirical work and theoretical models have greatly advanced our understanding of how populations navigate rugged fitness…

种群与进化 · 定量生物学 2026-04-21 Malvika Srivastava , Claudia Bank , Joachim Krug , Suman G. Das

Genotypic fitness landscapes are constructed by assessing the fitness of all possible combinations of a given number of mutations. In the last years, several experimental fitness landscapes have been completely resolved. As fitness…

Molecular evolution is often conceptualised as adaptive walks on rugged fitness landscapes, driven by mutations and constrained by incremental fitness selection. It is well known that epistasis shapes the ruggedness of the landscape's…

种群与进化 · 定量生物学 2022-11-03 Leonardo Trujillo , Paul Banse , Guillaume Beslon

A fitness landscape is a mapping from the space of genetic sequences, which is modeled here as a binary hypercube of dimension $L$, to the real numbers. We consider random models of fitness landscapes, where fitness values are assigned…

种群与进化 · 定量生物学 2015-06-16 Benjamin Schmiegelt , Joachim Krug

Evolvability refers to the ability of an individual genotype (solution) to produce offspring with mutually diverse phenotypes. Recent research has demonstrated that divergent search methods, particularly novelty search, promote evolvability…

神经与进化计算 · 计算机科学 2023-06-19 Bruno Gašperov , Marko Đurasević

The fitness landscape - the mapping between genotypes and fitness - determines properties of the process of adaptation. Several small genetic fitness landscapes have recently been built by selecting a handful of beneficial mutations and…

种群与进化 · 定量生物学 2014-05-15 François Blanquart , Guillaume Achaz , Thomas Bataillon , Olivier Tenaillon

Darwinian evolution is driven by random mutations, genetic recombination (gene shuffling) and selection that favors genotypes with high fitness. For systems where each genotype can be represented as a bitstring of length $L$, an overview of…

种群与进化 · 定量生物学 2023-04-11 Kristina Crona , Joachim Krug , Malvika Srivastava

Fitness landscapes are genotype to fitness mappings commonly used in evolutionary biology and computer science which are closely related to spin glass models. In this paper, we study the NK model for fitness landscapes where the interaction…

种群与进化 · 定量生物学 2015-06-12 Stefan Nowak , Joachim Krug

In this article a tool for the analysis of population-based EAs is used to derive asymptotic upper bounds on the optimization time of the algorithm solving Royal Roads problem, a test function with plateaus of fitness. In addition to this,…

神经与进化计算 · 计算机科学 2013-09-03 Aram Ter-Sarkisov , Stephen Marsland

The fitness landscape defines the relationship between genotypes and fitness in a given environment, and underlies fundamental quantities such as the distribution of selection coefficient, or the magnitude and type of epistasis. A better…

种群与进化 · 定量生物学 2016-05-18 François Blanquart , Thomas Bataillon

Proteins evolve through complex sequence spaces, with fitness landscapes serving as a conceptual framework that links sequence to function. Fitness landscapes can be smooth, where multiple similarly accessible evolutionary paths are…

A significant challenge in nature-inspired algorithmics is the identification of specific characteristics of problems that make them harder (or easier) to solve using specific methods. The hope is that, by identifying these characteristics,…

神经与进化计算 · 计算机科学 2013-05-06 Matthew Crossley , Andy Nisbet , Martyn Amos

This research presents a novel application of Evolutionary Computation to the domain of residential electric vehicle (EV) energy management. While reinforcement learning (RL) achieves high performance in vehicle-to-grid (V2G) optimization,…

神经与进化计算 · 计算机科学 2026-02-10 Vishesh Purnananda , Benjamin John Wruck , Mingyu Guo

Experimental studies on enzyme evolution show that only a small fraction of all possible mutation trajectories are accessible to evolution. However, these experiments deal with individual enzymes and explore a tiny part of the fitness…

种群与进化 · 定量生物学 2015-05-30 Alexander E. Lobkovsky , Yuri I. Wolf , Eugene V. Koonin

Much of the current theory of adaptation is based on Gillespie's mutational landscape model (MLM), which assumes that the fitness values of genotypes linked by single mutational steps are independent random variables. On the other hand, a…

种群与进化 · 定量生物学 2014-11-11 Johannes Neidhart , Ivan G. Szendro , Joachim Krug

Evolution is a dynamic process. The two classical forces of evolution are mutation and selection. Assuming small mutation rates, evolution can be predicted based solely on the fitness differences between phenotypes. Predicting an…

种群与进化 · 定量生物学 2015-03-23 Benedikt Bauer , Chaitanya S. Gokhale

The enormous size and complexity of genotypic sequence space frequently requires consideration of coarse-grained sequences in empirical models. We develop scaling relations to quantify the effect of this coarse-graining on properties of…

种群与进化 · 定量生物学 2015-06-01 Michael Manhart , Alexandre V. Morozov