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Recent Advances in the Theory and Application of Fitness Landscapes

Part of the Emergence, Complexity and Computation Book Series (volume 6)

Editors: Richter, Hendrik; Engelbrecht, Andries

DOI: 10.1007/978-3-642-41888-4

ISBN: 978-3-642-41887-7

Publisher: Springer Berlin Heidelberg - Springer Journals

Jan 1, 2014

1 - 10 of 20 Chapters

Available

Fitness Landscapes: From Evolutionary Biology to Evolutionary Computation

Richter, Hendrik

Pages: 3 –31

[This chapter gives an introduction to the book and an overview of fundamental concepts, notions and mathematical descriptions of fitness landscapes. Based on a brief discussion of the origin of landscape paradigms, major motivations to use fitness landscapes are presented. It is further...
Available

Fundamental Principles of Control Landscapes with Applications to Quantum Mechanics, Chemistry and Evolution

Rabitz, Herschel; Wu, Re-Bing; Ho, Tak-San; Tibbetts, Katharine Moore; Feng, Xiaojiang

Pages: 33 –70

[The concept of a landscape or response surface naturally arises in applications widely ranging over the sciences, engineering and other disciplines. A landscape is the desired output as a function of a set of input variables, often of very high dimension. The relationship between the features of...
Available

Biomolecular Information Gained through In Vitro Evolution on a Fitness Landscape in Sequence Space

Aita, Takuyo; Husimi, Yuzuru

Pages: 71 –100

[Biological evolution at the molecular level is conceptually regarded as the genetic information gaining process. Analyzing the in vitro evolution process, which is a simplified Darwinian evolution under a well-controlled environment, we can clarify the concept of the information gaining process....
Available

Fitness Landscape Analysis for Metaheuristic Performance Prediction

Malan, Katherine M.; Engelbrecht, Andries P.

Pages: 103 –132

[Metaheuristics have become popular for solving complex optimisation problems where classical techniques are either infeasible or perform poorly. Despite many success stories, it is well known that metaheuristics sometimes fail and that researchers and practitioners frequently resort to trial and...
Available

Fitness Landscapes and Problem Difficulty in Evolutionary Algorithms: From Theory to Applications

Lu, Guanzhou; Li, Jinlong; Yao, Xin

Pages: 133 –152

[Above many successes of evolutionary algorithms in solving computationally hard optimisations problems, a major challenge in practice remains how to select/construct the best suited algorithm when solving a problem. The well-known no free lunch theorem rules out the possibility of developing one...
Available

Geometry and Coarse-Grained Representations of Landscapes

Klemm, Konstantin; Qin, Jing; Stadler, Peter F.

Pages: 153 –176

[Basic geometric notions describing the structure of landscapes as well as the dynamics of local search on them include basins, saddles, reachability and funnels. We focus on discrete, combinatorial landscapes and emphasize the complications arising from local degeneracies. Local search in such...
Available

Polytopes, Graphs and Fitness Landscapes

Crona, Kristina

Pages: 177 –205

[Darwinian evolution can be illustrated as an uphill walk in a landscape, where the surface consists of genotypes, the height coordinates represent fitness, and each step corresponds to a point mutation. Epistasis, roughly defined as the dependence between the fitness effects of mutations, is a...
Available

Estimating the Degree of Neutrality and Ruggedness of Fitness Landscapes

Katada, Yoshiaki

Pages: 207 –231

[In recent years, not only ruggedness but also neutrality has been recognized as an important feature of a fitness landscape for genetic search. As it has been reported that the evolutionary dynamics on a fitness landscape with neutrality is clearly different from the canonical explanations,...
Available

Local Optima Networks: A New Model of Combinatorial Fitness Landscapes

Ochoa, Gabriela; Verel, Sébastien; Daolio, Fabio; Tomassini, Marco

Pages: 233 –262

[This chapter overviews a recently introduced network-based model of combinatorial landscapes: Local Optima Networks (LON). The model compresses the information given by the whole search space into a smaller mathematical object that is a graph having as vertices the local optima and as edges the...
Available

Fitness Landscapes That Depend on Time

Richter, Hendrik

Pages: 265 –299

[Landscapes whose fitness values change with time occur in several contexts. A first is that the evolutionary process takes place in a dynamic environment. Dynamics may be connected to optimization problems with changing objective functions, or generally that conditions apart from the genetic...

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