Author: Ellen Baake
Publisher:
ISBN: 9783985475056
Category :
Languages : en
Pages :
Book Description
Probabilistic Structures in Evolution
Genetic Algorithms + Data Structures = Evolution Programs
Author: Zbigniew Michalewicz
Publisher: Springer Science & Business Media
ISBN: 3662028301
Category : Mathematics
Languages : en
Pages : 257
Book Description
'What does your Master teach?' asked a visitor. 'Nothing,' said the disciple. 'Then why does he give discourses?' 'He only points the way - he teaches nothing.' Anthony de Mello, One Minute Wisdom During the last three decades there has been a growing interest in algorithms which rely on analogies to natural processes. The emergence of massively par allel computers made these algorithms of practical interest. The best known algorithms in this class include evolutionary programming, genetic algorithms, evolution strategies, simulated annealing, classifier systems, and neural net works. Recently (1-3 October 1990) the University of Dortmund, Germany, hosted the First Workshop on Parallel Problem Solving from Nature [164]. This book discusses a subclass of these algorithms - those which are based on the principle of evolution (survival of the fittest). In such algorithms a popu lation of individuals (potential solutions) undergoes a sequence of unary (muta tion type) and higher order (crossover type) transformations. These individuals strive for survival: a selection scheme, biased towards fitter individuals, selects the next generation. After some number of generations, the program converges - the best individual hopefully represents the optimum solution. There are many different algorithms in this category. To underline the sim ilarities between them we use the common term "evolution programs" .
Publisher: Springer Science & Business Media
ISBN: 3662028301
Category : Mathematics
Languages : en
Pages : 257
Book Description
'What does your Master teach?' asked a visitor. 'Nothing,' said the disciple. 'Then why does he give discourses?' 'He only points the way - he teaches nothing.' Anthony de Mello, One Minute Wisdom During the last three decades there has been a growing interest in algorithms which rely on analogies to natural processes. The emergence of massively par allel computers made these algorithms of practical interest. The best known algorithms in this class include evolutionary programming, genetic algorithms, evolution strategies, simulated annealing, classifier systems, and neural net works. Recently (1-3 October 1990) the University of Dortmund, Germany, hosted the First Workshop on Parallel Problem Solving from Nature [164]. This book discusses a subclass of these algorithms - those which are based on the principle of evolution (survival of the fittest). In such algorithms a popu lation of individuals (potential solutions) undergoes a sequence of unary (muta tion type) and higher order (crossover type) transformations. These individuals strive for survival: a selection scheme, biased towards fitter individuals, selects the next generation. After some number of generations, the program converges - the best individual hopefully represents the optimum solution. There are many different algorithms in this category. To underline the sim ilarities between them we use the common term "evolution programs" .
Understanding Evolution
Author: Kostas Kampourakis
Publisher: Cambridge University Press
ISBN: 1107034914
Category : Science
Languages : en
Pages : 275
Book Description
Bringing together conceptual obstacles and core concepts of evolutionary theory, this book presents evolution as straightforward and intuitive.
Publisher: Cambridge University Press
ISBN: 1107034914
Category : Science
Languages : en
Pages : 275
Book Description
Bringing together conceptual obstacles and core concepts of evolutionary theory, this book presents evolution as straightforward and intuitive.
Darwin's Doubt
Author: Stephen C. Meyer
Publisher: Harper Collins
ISBN: 0062071491
Category : Science
Languages : en
Pages : 605
Book Description
When Charles Darwin finished The Origin of Species, he thought that he had explained every clue, but one. Though his theory could explain many facts, Darwin knew that there was a significant event in the history of life that his theory did not explain. During this event, the “Cambrian explosion,” many animals suddenly appeared in the fossil record without apparent ancestors in earlier layers of rock. In Darwin’s Doubt, Stephen C. Meyer tells the story of the mystery surrounding this explosion of animal life—a mystery that has intensified, not only because the expected ancestors of these animals have not been found, but because scientists have learned more about what it takes to construct an animal. During the last half century, biologists have come to appreciate the central importance of biological information—stored in DNA and elsewhere in cells—to building animal forms. Expanding on the compelling case he presented in his last book, Signature in the Cell, Meyer argues that the origin of this information, as well as other mysterious features of the Cambrian event, are best explained by intelligent design, rather than purely undirected evolutionary processes.
Publisher: Harper Collins
ISBN: 0062071491
Category : Science
Languages : en
Pages : 605
Book Description
When Charles Darwin finished The Origin of Species, he thought that he had explained every clue, but one. Though his theory could explain many facts, Darwin knew that there was a significant event in the history of life that his theory did not explain. During this event, the “Cambrian explosion,” many animals suddenly appeared in the fossil record without apparent ancestors in earlier layers of rock. In Darwin’s Doubt, Stephen C. Meyer tells the story of the mystery surrounding this explosion of animal life—a mystery that has intensified, not only because the expected ancestors of these animals have not been found, but because scientists have learned more about what it takes to construct an animal. During the last half century, biologists have come to appreciate the central importance of biological information—stored in DNA and elsewhere in cells—to building animal forms. Expanding on the compelling case he presented in his last book, Signature in the Cell, Meyer argues that the origin of this information, as well as other mysterious features of the Cambrian event, are best explained by intelligent design, rather than purely undirected evolutionary processes.
Mathematics of Evolution and Phylogeny
Author: Olivier Gascuel
Publisher: OUP Oxford
ISBN: 9780191513732
Category : Mathematics
Languages : en
Pages : 444
Book Description
This book considers evolution at different scales: sequences, genes, gene families, organelles, genomes and species. The focus is on the mathematical and computational tools and concepts, which form an essential basis of evolutionary studies, indicate their limitations, and give them orientation. Recent years have witnessed rapid progress in the mathematics of evolution and phylogeny, with models and methods becoming more realistic, powerful, and complex. Aimed at graduates and researchers in phylogenetics, mathematicians, computer scientists and biologists, and including chapters by leading scientists: A. Bergeron, D. Bertrand, D. Bryant, R. Desper, O. Elemento, N. El-Mabrouk, N. Galtier, O. Gascuel, M. Hendy, S. Holmes, K. Huber, A. Meade, J. Mixtacki, B. Moret, E. Mossel, V. Moulton, M. Pagel, M.-A. Poursat, D. Sankoff, M. Steel, J. Stoye, J. Tang, L.-S. Wang, T. Warnow, Z. Yang, this book of contributed chapters explains the basis and covers the recent results in this highly topical area.
Publisher: OUP Oxford
ISBN: 9780191513732
Category : Mathematics
Languages : en
Pages : 444
Book Description
This book considers evolution at different scales: sequences, genes, gene families, organelles, genomes and species. The focus is on the mathematical and computational tools and concepts, which form an essential basis of evolutionary studies, indicate their limitations, and give them orientation. Recent years have witnessed rapid progress in the mathematics of evolution and phylogeny, with models and methods becoming more realistic, powerful, and complex. Aimed at graduates and researchers in phylogenetics, mathematicians, computer scientists and biologists, and including chapters by leading scientists: A. Bergeron, D. Bertrand, D. Bryant, R. Desper, O. Elemento, N. El-Mabrouk, N. Galtier, O. Gascuel, M. Hendy, S. Holmes, K. Huber, A. Meade, J. Mixtacki, B. Moret, E. Mossel, V. Moulton, M. Pagel, M.-A. Poursat, D. Sankoff, M. Steel, J. Stoye, J. Tang, L.-S. Wang, T. Warnow, Z. Yang, this book of contributed chapters explains the basis and covers the recent results in this highly topical area.
EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation III
Author: Oliver Schuetze
Publisher: Springer
ISBN: 3319014609
Category : Technology & Engineering
Languages : en
Pages : 268
Book Description
This book comprises a selection of extended abstracts and papers presented at the EVOLVE 2012 held in Mexico City, Mexico. The aim of the EVOLVE is to build a bridge between probability, set oriented numerics, and evolutionary computation as to identify new common and challenging research aspects. The conference is also intended to foster a growing interest for robust and efficient methods with a sound theoretical background. EVOLVE aims to unify theory-inspired methods and cutting-edge techniques ensuring performance guarantee factors. By gathering researchers with different backgrounds, a unified view and vocabulary can emerge where the theoretical advancements may echo in different domains. Summarizing, the EVOLVE conference focuses on challenging aspects arising at the passage from theory to new paradigms and aims to provide a unified view while raising questions related to reliability, performance guarantees, and modeling. The extended papers of the EVOLVE 2012 make a contribution to this goal.
Publisher: Springer
ISBN: 3319014609
Category : Technology & Engineering
Languages : en
Pages : 268
Book Description
This book comprises a selection of extended abstracts and papers presented at the EVOLVE 2012 held in Mexico City, Mexico. The aim of the EVOLVE is to build a bridge between probability, set oriented numerics, and evolutionary computation as to identify new common and challenging research aspects. The conference is also intended to foster a growing interest for robust and efficient methods with a sound theoretical background. EVOLVE aims to unify theory-inspired methods and cutting-edge techniques ensuring performance guarantee factors. By gathering researchers with different backgrounds, a unified view and vocabulary can emerge where the theoretical advancements may echo in different domains. Summarizing, the EVOLVE conference focuses on challenging aspects arising at the passage from theory to new paradigms and aims to provide a unified view while raising questions related to reliability, performance guarantees, and modeling. The extended papers of the EVOLVE 2012 make a contribution to this goal.
The Probabilistic Method
Author: Noga Alon
Publisher: John Wiley & Sons
ISBN: 1119062071
Category : Mathematics
Languages : en
Pages : 396
Book Description
Praise for the Third Edition “Researchers of any kind of extremal combinatorics or theoretical computer science will welcome the new edition of this book.” - MAA Reviews Maintaining a standard of excellence that establishes The Probabilistic Method as the leading reference on probabilistic methods in combinatorics, the Fourth Edition continues to feature a clear writing style, illustrative examples, and illuminating exercises. The new edition includes numerous updates to reflect the most recent developments and advances in discrete mathematics and the connections to other areas in mathematics, theoretical computer science, and statistical physics. Emphasizing the methodology and techniques that enable problem-solving, The Probabilistic Method, Fourth Edition begins with a description of tools applied to probabilistic arguments, including basic techniques that use expectation and variance as well as the more advanced applications of martingales and correlation inequalities. The authors explore where probabilistic techniques have been applied successfully and also examine topical coverage such as discrepancy and random graphs, circuit complexity, computational geometry, and derandomization of randomized algorithms. Written by two well-known authorities in the field, the Fourth Edition features: Additional exercises throughout with hints and solutions to select problems in an appendix to help readers obtain a deeper understanding of the best methods and techniques New coverage on topics such as the Local Lemma, Six Standard Deviations result in Discrepancy Theory, Property B, and graph limits Updated sections to reflect major developments on the newest topics, discussions of the hypergraph container method, and many new references and improved results The Probabilistic Method, Fourth Edition is an ideal textbook for upper-undergraduate and graduate-level students majoring in mathematics, computer science, operations research, and statistics. The Fourth Edition is also an excellent reference for researchers and combinatorists who use probabilistic methods, discrete mathematics, and number theory. Noga Alon, PhD, is Baumritter Professor of Mathematics and Computer Science at Tel Aviv University. He is a member of the Israel National Academy of Sciences and Academia Europaea. A coeditor of the journal Random Structures and Algorithms, Dr. Alon is the recipient of the Polya Prize, The Gödel Prize, The Israel Prize, and the EMET Prize. Joel H. Spencer, PhD, is Professor of Mathematics and Computer Science at the Courant Institute of New York University. He is the cofounder and coeditor of the journal Random Structures and Algorithms and is a Sloane Foundation Fellow. Dr. Spencer has written more than 200 published articles and is the coauthor of Ramsey Theory, Second Edition, also published by Wiley.
Publisher: John Wiley & Sons
ISBN: 1119062071
Category : Mathematics
Languages : en
Pages : 396
Book Description
Praise for the Third Edition “Researchers of any kind of extremal combinatorics or theoretical computer science will welcome the new edition of this book.” - MAA Reviews Maintaining a standard of excellence that establishes The Probabilistic Method as the leading reference on probabilistic methods in combinatorics, the Fourth Edition continues to feature a clear writing style, illustrative examples, and illuminating exercises. The new edition includes numerous updates to reflect the most recent developments and advances in discrete mathematics and the connections to other areas in mathematics, theoretical computer science, and statistical physics. Emphasizing the methodology and techniques that enable problem-solving, The Probabilistic Method, Fourth Edition begins with a description of tools applied to probabilistic arguments, including basic techniques that use expectation and variance as well as the more advanced applications of martingales and correlation inequalities. The authors explore where probabilistic techniques have been applied successfully and also examine topical coverage such as discrepancy and random graphs, circuit complexity, computational geometry, and derandomization of randomized algorithms. Written by two well-known authorities in the field, the Fourth Edition features: Additional exercises throughout with hints and solutions to select problems in an appendix to help readers obtain a deeper understanding of the best methods and techniques New coverage on topics such as the Local Lemma, Six Standard Deviations result in Discrepancy Theory, Property B, and graph limits Updated sections to reflect major developments on the newest topics, discussions of the hypergraph container method, and many new references and improved results The Probabilistic Method, Fourth Edition is an ideal textbook for upper-undergraduate and graduate-level students majoring in mathematics, computer science, operations research, and statistics. The Fourth Edition is also an excellent reference for researchers and combinatorists who use probabilistic methods, discrete mathematics, and number theory. Noga Alon, PhD, is Baumritter Professor of Mathematics and Computer Science at Tel Aviv University. He is a member of the Israel National Academy of Sciences and Academia Europaea. A coeditor of the journal Random Structures and Algorithms, Dr. Alon is the recipient of the Polya Prize, The Gödel Prize, The Israel Prize, and the EMET Prize. Joel H. Spencer, PhD, is Professor of Mathematics and Computer Science at the Courant Institute of New York University. He is the cofounder and coeditor of the journal Random Structures and Algorithms and is a Sloane Foundation Fellow. Dr. Spencer has written more than 200 published articles and is the coauthor of Ramsey Theory, Second Edition, also published by Wiley.
Probabilistic Mechanics of Quasibrittle Structures
Author: Zdenek P. Bazant
Publisher: Cambridge University Press
ISBN: 1107151708
Category : Science
Languages : en
Pages : 319
Book Description
This book presents an experimentally validated probabilistic strength theory of structures made of concrete, composites, ceramics and other quasibrittle materials.
Publisher: Cambridge University Press
ISBN: 1107151708
Category : Science
Languages : en
Pages : 319
Book Description
This book presents an experimentally validated probabilistic strength theory of structures made of concrete, composites, ceramics and other quasibrittle materials.
Evolutionary Genomics
Author: Maria Anisimova
Publisher: Humana Press
ISBN: 9781617795848
Category : Medical
Languages : en
Pages : 556
Book Description
Together with early theoretical work in population genetics, the debate on sources of genetic makeup initiated by proponents of the neutral theory made a solid contribution to the spectacular growth in statistical methodologies for molecular evolution. Evolutionary Genomics: Statistical and Computational Methods is intended to bring together the more recent developments in the statistical methodology and the challenges that followed as a result of rapidly improving sequencing technologies. Presented by top scientists from a variety of disciplines, the collection includes a wide spectrum of articles encompassing theoretical works and hands-on tutorials, as well as many reviews with key biological insight. Volume 2 begins with phylogenomics and continues with in-depth coverage of natural selection, recombination, and genomic innovation. The remaining chapters treat topics of more recent interest, including population genomics, -omics studies, and computational issues related to the handling of large-scale genomic data. Written in the highly successful Methods in Molecular BiologyTM series format, this work provides the kind of advice on methodology and implementation that is crucial for getting ahead in genomic data analyses. Comprehensive and cutting-edge, Evolutionary Genomics: Statistical and Computational Methods is a treasure chest of state-of the-art methods to study genomic and omics data, certain to inspire both young and experienced readers to join the interdisciplinary field of evolutionary genomics.
Publisher: Humana Press
ISBN: 9781617795848
Category : Medical
Languages : en
Pages : 556
Book Description
Together with early theoretical work in population genetics, the debate on sources of genetic makeup initiated by proponents of the neutral theory made a solid contribution to the spectacular growth in statistical methodologies for molecular evolution. Evolutionary Genomics: Statistical and Computational Methods is intended to bring together the more recent developments in the statistical methodology and the challenges that followed as a result of rapidly improving sequencing technologies. Presented by top scientists from a variety of disciplines, the collection includes a wide spectrum of articles encompassing theoretical works and hands-on tutorials, as well as many reviews with key biological insight. Volume 2 begins with phylogenomics and continues with in-depth coverage of natural selection, recombination, and genomic innovation. The remaining chapters treat topics of more recent interest, including population genomics, -omics studies, and computational issues related to the handling of large-scale genomic data. Written in the highly successful Methods in Molecular BiologyTM series format, this work provides the kind of advice on methodology and implementation that is crucial for getting ahead in genomic data analyses. Comprehensive and cutting-edge, Evolutionary Genomics: Statistical and Computational Methods is a treasure chest of state-of the-art methods to study genomic and omics data, certain to inspire both young and experienced readers to join the interdisciplinary field of evolutionary genomics.
Optimal Reliability-Based Design of Structures Against Several Natural Hazards
Author: Alfredo H-S Ang
Publisher: CRC Press
ISBN: 1000461823
Category : Technology & Engineering
Languages : en
Pages : 71
Book Description
Interest in the topic of structural reliability and optimal design has been rapidly growing in recent years. Besides, the field of numerical methods and artificial intelligence is experiencing a surge of new methods and the refinement of existing ones to expand opportunities to apply robust formulations to complex engineering problems. Today, more than ever, the field is receiving fresh ideas on how to face the challenges of finding a balance between cost and benefits that may lead towards the optimal design of systems. Recently, the probability density evolution method (PDEM) was proposed by Prof. Jie Li as an alternative way to obtain the stochastic and dynamic solution of the safety level of engineering systems under any kind of hazard. This work deals with the application of this powerful method to derive optimal design recommendations for large engineering systems under natural hazards. The three case studies illustrate to engineers and academic specialists how to strike a cost-effective balance in designing such systems.
Publisher: CRC Press
ISBN: 1000461823
Category : Technology & Engineering
Languages : en
Pages : 71
Book Description
Interest in the topic of structural reliability and optimal design has been rapidly growing in recent years. Besides, the field of numerical methods and artificial intelligence is experiencing a surge of new methods and the refinement of existing ones to expand opportunities to apply robust formulations to complex engineering problems. Today, more than ever, the field is receiving fresh ideas on how to face the challenges of finding a balance between cost and benefits that may lead towards the optimal design of systems. Recently, the probability density evolution method (PDEM) was proposed by Prof. Jie Li as an alternative way to obtain the stochastic and dynamic solution of the safety level of engineering systems under any kind of hazard. This work deals with the application of this powerful method to derive optimal design recommendations for large engineering systems under natural hazards. The three case studies illustrate to engineers and academic specialists how to strike a cost-effective balance in designing such systems.