Applied Evolutionary Algorithms in Java


I’ve found out a new book in the University of Cantabria Library that, I think, it’s going to be very useful in my Evolutionary Computation course.

Applied Evolutionary Algorithms in Java (see Amazon Reference)

Robert Ghanea-Hercock
BTexact Technologies
Intelligent Systems Laboratory

2003 Springer Verlag New York

In the (hard) book’s back cover we can devise the content and purpose of this (I think) interesting and practical book:

Evolutionary Algorithms provide a powerful range of methods for solving complex engineering search and optimization problems. However, the relative complexity of the principles underlying evolution-based methods has for the last decades prevented their rapid acceptance as en element of computing techniques.

Applied Evolutionary Algorithms in Java provides the reader with a practical, hands-on approach to applying evolutionary algorithms to computer engineering and scientific problems. The book explains key concepts through clear examples, ranging from simple to more complex problem domains, and all based on real world industrial problems. It employs a Java-based toolkit for exploring a range of genetic-algorithm techniques. This toolkit provides an easy-to-use visual interface, with integrated graphing and analysis tools. A modes knowledge of basic algebra and graph methods will suffice for a thorough understanding of all material.

Topics and featrures

* Includes a complete Java Toolkit for exploring evolutionary algorithms
* Covers the major evolutionary algorithms in common usage
* Numerous examples from image processing, fuzzy-logic control systems, mobile robots and telecommunication-network optimization problems
* Utilizes many visualisation techniques, to increase understanding
* Accompanying CD-ROM features full code for the Java toolkit, as well as open-source Java code libraries for evolutionary applications and robot simulators

Written by a leading R&D researcher in the field, and with clarity of presentation and numerous examples, this book makes technical material easy to grasp. It is an ideally suited resource for computer scientists, practitioners, and researchers with an interest in studying or tapping the power of evolutionary algorithms in their work and research.

The book includes a CDROM with source code material of the chapters in the book. In Preface, the author says:

A major aspect of this text is the use of a Java toolkit for exploring Genetic Algorithms, with examples in digital image processing and mobile robot control. A hands-on approach is encouraged throughout the text, in order to develop an intuitive understanding of evlution-driven algorithms. The toolkit provides an easy-to-use visual interface, with integrated graphing and analysis tools, which aid in the task of visualising the underlying processes. Full code for the toolkit is available from the author’s web site, where regular updates can be found, and on the included CDROM.

I’ve seen that the supposed author’s web site cited in Preface is out of order now.

Appendices are also very interesting in the book. Appendix A provides a listing of some useful web-based references and software (ECJ, EOS, GA PlayGround, JGProg, …) Appendix B describes the specific genetic algorithm software used in the text, GPSYS Java GP Package written by Adil Qureshi, and the EOS Evolution Toolkit from the Intelligent Systems Labs at BTexact Technologies. Appendix C provides some essential background knowledge in Fuzzy Logic, which is required for the mobile robot control example. Appendix D is a detailed used guide for the excellent mobile robot simulator (Rossum’s Playhouse RP1 from The Rossum’s Project), which has been generously contributed by Gary Lucas.

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