Book description
An essential capacity of intelligence is the ability to learn. An artificially intelligent system that could learn would not have to be programmed for every eventuality; it could adapt to its changing environment and conditions just as biological systems do. Illustrating Evolutionary Computation with Mathematica introduces evolutionary computation to the technically savvy reader who wishes to explore this fascinating and increasingly important field. Unique among books on evolutionary computation, the book also explores the application of evolution to developmental processes in nature, such as the growth processes in cells and plants. If you are a newcomer to the evolutionary computation field, an engineer, a programmer, or even a biologist wanting to learn how to model the evolution and coevolution of plants, this book will provide you with a visually rich and engaging account of this complex subject.
* Introduces the major mechanisms of biological evolution.
* Demonstrates many fascinating aspects of evolution in nature with simple, yet illustrative examples.
* Explains each of the major branches of evolutionary computation: genetic algorithms, genetic programming, evolutionary programming, and evolution strategies.
* Demonstrates the programming of computers by evolutionary principles using Evolvica, a genetic programming system designed by the author.
* Shows in detail how to evolve developmental programs modeled by cellular automata and Lindenmayer systems.
* Provides Mathematica notebooks on the Web that include all the programs in the book and supporting animations, movies, and graphics.
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- Preface: From Darwin to an ArtFlowers Garden
- Chapter 1: Introduction: The Fascination of Evolution
- Part I: Evolutionary Computation
-
Part II: If Darwin Had Been a Programmer…
- Part II: Introduction to If Darwin Had Been a Programmer…
- Chapter 5: Programming by Evolution
-
Chapter 6: Evolutionary Programming
- 6.1 Computer programs as finite state machines
- 6.2 Mutation operators on FSA
- 6.3 Automatic generation of finite state machines
- 6.4 EP selection and evolution scheme
- 6.5 Evolutionary programming with Evolvica
- 6.6 Evolutionary programming at work
- 6.7 Diversification of evolutionary programming
- 6.8 Bibliographical notes
- Chapter 7: Genetic Programming
- Chapter 8: Advanced Genetic Programming at Work
- Part III: Evolution of Developmental Programs
- References
- Index
Product information
- Title: Illustrating Evolutionary Computation with Mathematica
- Author(s):
- Release date: February 2001
- Publisher(s): Morgan Kaufmann
- ISBN: 9780080508450
You might also like
book
Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing
Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some …
book
Mathematica DeMYSTiFied
Need to learn MATHEMATICA? Problem SOLVED! Take full advantage of all the powerful capabilities of Mathematica …
book
An Engineer's Guide to Mathematica
Free Mathematica 10 Update Included! Now available from www.wiley.com/go/magrab Updated material includes: - Creating regions and …
book
Raspbian OS Programming with the Raspberry Pi: IoT Projects with Wolfram, Mathematica, and Scratch
Master the command line and Raspbian Linux as well as the physical connections of the Pi. …