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Dual Phase Evolution : From Theory to Practice.

By: Abbass, Hussein A.
Contributor(s): Green, David G | Liu, Jing.
Material type: TextTextSeries: eBooks on Demand.Publisher: New York, NY : Springer, 2013Copyright date: ©2014Edition: 1st ed.Description: 1 online resource (210 pages).Content type: text Media type: computer Carrier type: online resourceISBN: 9781441984234.Subject(s): Natural computation.;Evolutionary computation.;Neural networks (Computer science)Genre/Form: Electronic books.Additional physical formats: Print version:: Dual Phase Evolution : From Theory to PracticeDDC classification: 530.474 LOC classification: TA1-2040Online resources: Click here to view this ebook.
Contents:
Intro -- Preface -- Acknowledgments -- Contents -- Figures -- Tables -- Acronyms -- Algorithms -- Symbols -- Part IDual Phase Evolution: An Introduction -- 1 Dual-Phase Evolution -- 1.1 Introduction -- 1.2 Complex Systems -- 1.2.1 Complexity -- 1.2.2 Emergence -- 1.2.3 Measures of Complexity -- 1.2.4 Complexity Paradigms -- 1.3 Networks and Phases -- 1.3.1 The Universality of Networks -- 1.3.2 The Connectivity Avalanche -- 1.4 Evolution -- 1.4.1 Natural Selection -- 1.4.2 Punctuated Equilibrium -- 1.4.3 Evolutionary History -- 1.5 Dual-Phase Evolution -- 1.6 DPE in Natural Systems -- 1.6.1 Materials and Physical Systems -- 1.6.2 Socioeconomic Networks -- 1.6.3 DPE and the Influence of Media on Public Opinion -- 1.6.4 DPE and Social Structure -- 1.6.5 Cognition and Learning -- 1.6.6 Network Generation Models Based on DPE -- 1.6.7 Landscape Ecology -- 1.7 DPE and Self-Organization -- 1.7.1 Self-Organization and Emergence -- 1.7.2 The Adaptive Cycle -- 1.7.3 DPE and Self-Organized Criticality -- 1.8 Formation of Genetic Modularity via DPE -- References -- Part IIBasics of Networks and Problem Solving -- 2 Network Theory -- 2.1 Networks and Network Analysis -- 2.1.1 Network Topology -- 2.1.2 Power Law Degree Distribution -- 2.1.3 Clustering Coefficient -- 2.1.4 Small Worlds -- 2.1.5 Assortative Mixing -- 2.1.6 Modularity and Community Structure -- 2.1.7 Network Motifs -- 2.2 Computation and Complexity -- 2.2.1 Combinatorics -- 2.2.2 State Spaces -- 2.2.3 Phase Transitions in State Spaces -- 2.3 Network Generation -- 2.3.1 Erdős-Rényi Model -- 2.3.2 Small-World Network Generation Model -- 2.3.3 Scale-Free Network Generation Model -- 2.3.4 Community Network Generation Model -- 2.3.5 Network Rewiring Models -- References -- 3 Problem Solving and Evolutionary Computation -- 3.1 Search in Landscape -- 3.2 Optimization -- 3.3 Algorithms or Heuristics.
3.3.1 Types of Search Techniques -- 3.4 Generating Local Moves -- 3.4.1 Local Optimality Revisited -- 3.5 Optimization Search Techniques -- 3.5.1 One-Solution-at-a-Time Algorithms -- 3.5.2 One-Solution-at-a-Time Heuristics -- 3.5.3 Population-Based Stochastic Heuristics -- 3.6 Simulated Annealing -- 3.7 Evolutionary Computation -- 3.7.1 Structure of Evolutionary Algorithms -- 3.7.2 Branches of Evolutionary Algorithms -- 3.7.3 How does GA Converges Under Selection and Crossover? -- 3.7.4 The Ingredients of Evolutionary Computation -- 3.7.5 Constraints Handling Methods -- 3.7.6 Lamarckian Inheritance and the Baldwin Effect -- 3.7.7 The Cellular Genetic Algorithm -- 3.7.8 Evolutionary Computation and Complex Adaptive Systems -- References -- Part IIIDual Phase Evolution for Network Generation and Problem Solving -- 4 DPE for Network Generation -- 4.1 DPE-Nets: Network Generation Model Using DPE -- 4.1.1 Initialization -- 4.1.2 Interactions -- 4.1.3 Implementation of DPE-Nets -- 4.2 Properties of DPE-Nets -- 4.2.1 Community Structure -- 4.2.2 Degree Distribution -- 4.2.3 Clustering Coefficient -- 4.2.4 Small Worlds -- 4.2.5 Assortative Mixing -- 4.3 Conclusion -- References -- 5 DPE Networks and Evolutionary Dynamics -- 5.1 Introduction -- 5.2 Related Work -- 5.2.1 Populations Structured According to Regular Networks -- 5.2.2 Populations Structured According to Irregular Networks -- 5.3 Design of Experiments -- 5.3.1 Representing Population Structure as a Graph -- 5.3.2 Takeover Time -- 5.3.3 Selection Scheme -- 5.3.4 Node Update Policy -- 5.4 Results and Discussion -- 5.4.1 Takeover Times on Dynamic DPE-Nets -- 5.4.2 Dynamic DPE-Nets Versus Static DPE-Nets -- 5.4.3 DPE-Nets Versus Other Network Structures -- 5.4.4 Selection Scheme and Node Update Policy -- 5.5 Conclusion -- References -- 6 DPE for Problem Solving.
6.1 DPEA: Dual-Phase Evolutionary Algorithms -- 6.1.1 Related Work on EAs with Structured Populations -- 6.1.2 DPEAs -- 6.2 Experiments -- 6.2.1 One-Dimensional Ring Structure -- 6.2.2 Two-Dimensional Lattice Structure -- 6.2.3 Comparison with Small-World Structure -- 6.3 Conclusion -- References -- 7 Conclusion and Future Work -- A Evolutionary and Genetics Principles -- A.1 Genetics -- A.2 Inbreeding -- A.3 Heritability -- A.4 Variation and Random Drift -- References -- Index.
Summary: This book explores the concept of dual phase evolution, focusing on 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.
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Item type Current location Call number URL Status Date due Barcode
Electronic Book UT Tyler Online
Online
TA1-2040 (Browse shelf) https://ebookcentral.proquest.com/lib/uttyler/detail.action?docID=1592841 Available EBC1592841

Intro -- Preface -- Acknowledgments -- Contents -- Figures -- Tables -- Acronyms -- Algorithms -- Symbols -- Part IDual Phase Evolution: An Introduction -- 1 Dual-Phase Evolution -- 1.1 Introduction -- 1.2 Complex Systems -- 1.2.1 Complexity -- 1.2.2 Emergence -- 1.2.3 Measures of Complexity -- 1.2.4 Complexity Paradigms -- 1.3 Networks and Phases -- 1.3.1 The Universality of Networks -- 1.3.2 The Connectivity Avalanche -- 1.4 Evolution -- 1.4.1 Natural Selection -- 1.4.2 Punctuated Equilibrium -- 1.4.3 Evolutionary History -- 1.5 Dual-Phase Evolution -- 1.6 DPE in Natural Systems -- 1.6.1 Materials and Physical Systems -- 1.6.2 Socioeconomic Networks -- 1.6.3 DPE and the Influence of Media on Public Opinion -- 1.6.4 DPE and Social Structure -- 1.6.5 Cognition and Learning -- 1.6.6 Network Generation Models Based on DPE -- 1.6.7 Landscape Ecology -- 1.7 DPE and Self-Organization -- 1.7.1 Self-Organization and Emergence -- 1.7.2 The Adaptive Cycle -- 1.7.3 DPE and Self-Organized Criticality -- 1.8 Formation of Genetic Modularity via DPE -- References -- Part IIBasics of Networks and Problem Solving -- 2 Network Theory -- 2.1 Networks and Network Analysis -- 2.1.1 Network Topology -- 2.1.2 Power Law Degree Distribution -- 2.1.3 Clustering Coefficient -- 2.1.4 Small Worlds -- 2.1.5 Assortative Mixing -- 2.1.6 Modularity and Community Structure -- 2.1.7 Network Motifs -- 2.2 Computation and Complexity -- 2.2.1 Combinatorics -- 2.2.2 State Spaces -- 2.2.3 Phase Transitions in State Spaces -- 2.3 Network Generation -- 2.3.1 Erdős-Rényi Model -- 2.3.2 Small-World Network Generation Model -- 2.3.3 Scale-Free Network Generation Model -- 2.3.4 Community Network Generation Model -- 2.3.5 Network Rewiring Models -- References -- 3 Problem Solving and Evolutionary Computation -- 3.1 Search in Landscape -- 3.2 Optimization -- 3.3 Algorithms or Heuristics.

3.3.1 Types of Search Techniques -- 3.4 Generating Local Moves -- 3.4.1 Local Optimality Revisited -- 3.5 Optimization Search Techniques -- 3.5.1 One-Solution-at-a-Time Algorithms -- 3.5.2 One-Solution-at-a-Time Heuristics -- 3.5.3 Population-Based Stochastic Heuristics -- 3.6 Simulated Annealing -- 3.7 Evolutionary Computation -- 3.7.1 Structure of Evolutionary Algorithms -- 3.7.2 Branches of Evolutionary Algorithms -- 3.7.3 How does GA Converges Under Selection and Crossover? -- 3.7.4 The Ingredients of Evolutionary Computation -- 3.7.5 Constraints Handling Methods -- 3.7.6 Lamarckian Inheritance and the Baldwin Effect -- 3.7.7 The Cellular Genetic Algorithm -- 3.7.8 Evolutionary Computation and Complex Adaptive Systems -- References -- Part IIIDual Phase Evolution for Network Generation and Problem Solving -- 4 DPE for Network Generation -- 4.1 DPE-Nets: Network Generation Model Using DPE -- 4.1.1 Initialization -- 4.1.2 Interactions -- 4.1.3 Implementation of DPE-Nets -- 4.2 Properties of DPE-Nets -- 4.2.1 Community Structure -- 4.2.2 Degree Distribution -- 4.2.3 Clustering Coefficient -- 4.2.4 Small Worlds -- 4.2.5 Assortative Mixing -- 4.3 Conclusion -- References -- 5 DPE Networks and Evolutionary Dynamics -- 5.1 Introduction -- 5.2 Related Work -- 5.2.1 Populations Structured According to Regular Networks -- 5.2.2 Populations Structured According to Irregular Networks -- 5.3 Design of Experiments -- 5.3.1 Representing Population Structure as a Graph -- 5.3.2 Takeover Time -- 5.3.3 Selection Scheme -- 5.3.4 Node Update Policy -- 5.4 Results and Discussion -- 5.4.1 Takeover Times on Dynamic DPE-Nets -- 5.4.2 Dynamic DPE-Nets Versus Static DPE-Nets -- 5.4.3 DPE-Nets Versus Other Network Structures -- 5.4.4 Selection Scheme and Node Update Policy -- 5.5 Conclusion -- References -- 6 DPE for Problem Solving.

6.1 DPEA: Dual-Phase Evolutionary Algorithms -- 6.1.1 Related Work on EAs with Structured Populations -- 6.1.2 DPEAs -- 6.2 Experiments -- 6.2.1 One-Dimensional Ring Structure -- 6.2.2 Two-Dimensional Lattice Structure -- 6.2.3 Comparison with Small-World Structure -- 6.3 Conclusion -- References -- 7 Conclusion and Future Work -- A Evolutionary and Genetics Principles -- A.1 Genetics -- A.2 Inbreeding -- A.3 Heritability -- A.4 Variation and Random Drift -- References -- Index.

This book explores the concept of dual phase evolution, focusing on 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.

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