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2014 | Book

Dual-Phase Evolution Read chapter Read first chapter

Dual Phase Evolution

Authors: David G. Green, Jing Liu, Hussein A. Abbass

Publisher: Springer New York

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

The aim of the book is to lay out the foundations and provide a detailed treatment of the subject. It will focus on two main elements in dual phase evolution: the relationship between dual phase evolution and other phase transition phenomena and the advantages of dual phase evolution in evolutionary computation and complex adaptive systems. The book will provide a coherent picture of dual phase evolution that encompasses these two elements and frameworks, methods and techniques to use this concept for problem solving.

Table of Contents

Frontmatter

Dual Phase Evolution: An Introduction

Frontmatter
Chapter 1. Dual-Phase Evolution
Abstract
Dual-phase evolution (DPE) is a theory about evolutionary processes of different kinds. In this chapter, we present examples to show how it can explain a wide variety of different phenomena. In later chapters we will explore its application to evolutionary computation and other.
David G. Green, Jing Liu, Hussein A. Abbass

Basics of Networks and Problem Solving

Frontmatter
Chapter 2. Network Theory
Abstract
Networks are structures composed of sets of nodes and edges.
David G. Green, Jing Liu, Hussein A. Abbass
Chapter 3. Problem Solving and Evolutionary Computation
Abstract
Optimization algorithms impose an implicit network structure on fitness landscapes. For a given algorithm A operating on a problem that has a fitness landscape F, connections between solutions are defined by the transitions allowed by A.
David G. Green, Jing Liu, Hussein A. Abbass

Dual Phase Evolution for Network Generation and Problem Solving

Frontmatter
Chapter 4. DPE for Network Generation
Abstract
Many scientists have mainly focused their attention on growing networks in which a new node is added to networks with time [1]. However, as indicated by Jin et al. [2], growth models of this type are quite inappropriate as models of the growth of social networks, and one of the reasons is although new vertices are of course added to social networks all the time, the timescale on which people make and break social connections is much shorter than the timescale on which vertices join or leave the network.
David G. Green, Jing Liu, Hussein A. Abbass
Chapter 5. DPE Networks and Evolutionary Dynamics
Abstract
Classic evolutionary algorithms (EAs) use a single population (panmixia) of individuals and apply operators on them as a whole. To prevent EAs from concentrating on a small search space area, structured EAs have been proposed to as a means for improving the search properties, which started from the parallel implementation of EAs [1‐4]. This kind of EAs uses spatially structured populations in which any given individual has its own neighborhood. Usually, the size of the neighborhood is much smaller than the size of the population. In this way, instead of all the other individuals in the population being considered as potential mates as in panmictic populations, only those that are in the same neighborhood can interact.
David G. Green, Jing Liu, Hussein A. Abbass
Chapter 6. DPE for Problem Solving
Abstract
In the previous chapter, we introduced that the standard population used in EAs is the panmictic one, and structured populations have been proposed to as a means for improving the search properties because several researchers have suggested that EAs populations might have structures endowed with spatial features, like many natural populations.
David G. Green, Jing Liu, Hussein A. Abbass
Chapter 7. Conclusion and Future Work
Abstract
May be the word “complexity” does not stand out in our daily conversations. Its meaning, however, is inherent in many of our daily discussions. When we ask how did my child understand what I just said? or how did this person commit a murder when they lived a quiet decent life? When we see sudden transitions that make people and systems behave in a way that we have not seen before. When we see a single simple event cascades into a disastrous outcome. Complexity is pertaining in every event we encounter, every experience we live, and every surprise we face.
David G. Green, Jing Liu, Hussein A. Abbass
Backmatter
Metadata
Title
Dual Phase Evolution
Authors
David G. Green
Jing Liu
Hussein A. Abbass
Copyright Year
2014
Publisher
Springer New York
Electronic ISBN
978-1-4419-8423-4
Print ISBN
978-1-4419-8422-7
DOI
https://doi.org/10.1007/978-1-4419-8423-4

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