Science has made great strides in modeling space, time, mass and energy. Yet little attention has been paid to the precise representation of the information ubiquitous in nature.Introduction to Evolutionary Informatics fuses results from complexity modeling and information theory that allow both meaning and design difficulty in nature to be measured in bits. Built on the foundation of a series of peer-reviewed papers published by the authors, the book is written at a level easily understandable to readers with knowledge of rudimentary high school math. Those seeking a quick first read or those not interested in mathematical detail can skip marked sections in the monograph and still experience the impact of this new and exciting model of nature's information.This book is written for enthusiasts in science, engineering and mathematics interested in understanding the essential role of information in closely examined evolution theory.

"Science has made great strides in modeling space, time, mass and energy. Yet little attention has been paid to the precise representation of the information ubiquitous in nature. Introduction to Evolutionary Informatics fuses results from complexity modeling and information theory that allow both meaning and design difficulty in nature to be measured in bits. Built on the foundation of a series of peer-reviewed papers published by the authors, the book is written at a level easily understandable to readers with knowledge of rudimentary high school math. Those seeking a quick first read or those not interested in mathematical detail can skip marked sections in the monograph and still experience the impact of this new and exciting model of nature's information. This book is written for enthusiasts in science, engineering and mathematics interested in understanding the essential role of information in closely examined evolution theory."--Publisher's website.

The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.

Evolutionary algorithms are becoming increasingly attractive across various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science and economics. Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms. It covers such hot topics as: • genetic algorithms, • differential evolution, • swarm intelligence, and • artificial immune systems. The reader is introduced to a range of applications, as Introduction to Evolutionary Algorithms demonstrates how to model real world problems, how to encode and decode individuals, and how to design effective search operators according to the chromosome structures with examples of constraint optimization, multiobjective optimization, combinatorial optimization, and supervised/unsupervised learning. This emphasis on practical applications will benefit all students, whether they choose to continue their academic career or to enter a particular industry. Introduction to Evolutionary Algorithms is intended as a textbook or self-study material for both advanced undergraduates and graduate students. Additional features such as recommended further reading and ideas for research projects combine to form an accessible and interesting pedagogical approach to this widely used discipline.

Mathematics of Bioinformatics: Theory, Methods, and Applications provides a comprehensive format for connecting and integrating information derived from mathematical methods and applying it to the understanding of biological sequences, structures, and networks. Each chapter is divided into a number of sections based on the bioinformatics topics and related mathematical theory and methods. Each topic of the section is comprised of the following three parts: an introduction to the biological problems in bioinformatics; a presentation of relevant topics of mathematical theory and methods to the bioinformatics problems introduced in the first part; an integrative overview that draws the connections and interfaces between bioinformatics problems/issues and mathematical theory/methods/applications.

Ecological Informatics promotes interdisciplinary research between ecology and computer science on elucidation of principles of information processing in ecosystems, ecological sustainability by informed decision making, and bio-inspired computation. The 2nd edition of the book consolidates the scope, concepts, and techniques of this newly emerging discipline by a new preface and additional chapters on cellular automata, qualitative reasoning, hybrid evolutionary algorithms and artificial neural networks. It illustrates numerous applications of Ecological Informatics for aquatic and terrestrial ecosystems, image recognition at micro- and macro-scale as well as computer hardware design. Case studies focus on applications of artificial neural networks, evolutionary computation, cellular automata, adaptive agents, fuzzy logic as well as qualitative reasoning. The 2nd edition of the book includes an index with novel evolutionary algorithms for the discovery of multiple nonlinear functions and rule sets as well as parameter optimisation in complex ecological data.

Bioinformatics is a field which uses the principles and techniques of mathematics, computer science, engineering, statistics, etc. to analyse and interpret biological data. It is also used to understand the complex system of proteomics. The topics studied under this area are DNA sequencing, computational evolutionary biology, pan genomics, gene expression analysis, protein localization, structural bioinformatics, biodiversity informatics, etc. This book unfolds the innovative aspects of bioinformatics which will be crucial for the holistic understanding of the subject matter. It studies, analyses and upholds the pillars of this field and its utmost significance in modern times. This textbook will serve as a reference to a broad spectrum of readers.