Illustrating Evolutionary Computation With Mathematica (Hardcover)

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.

Features:

• 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.

Authors:

Christian Jacob is assistant professor in the Department of Computer Science at the University of Calgary. His areas of interest include evolutionary algorithms, Lindenmayer systems, ecosystems modeling, distributed computing, alternative programming paradigms, biocomputing, and bioinformatics. He is the author of the German edition of this book, Principia Evolvica Simulierte Evolution mit Mathematica, published by dpunkt.verlag.

Table of Contents:

Part 1: Fascinating Evolution

Part 2: Evolutionary Computation

Part 3: If Darwin was a Programmer

Part 4: Evolution of Developmental Programs

Related Titles:

Artificial Intelligence

訂購本書 | 作者 | 目錄 | 相關書籍

智能的一個重要能力是學習的能力。一個能夠學習的人工智能系統不需要為每一種情況進行編程；它可以像生物系統一樣適應不斷變化的環境和條件。《Illustrating Evolutionary Computation with Mathematica》向技術熟悉的讀者介紹了進化計算這一迷人且越來越重要的領域。與其他關於進化計算的書籍不同，本書還探討了進化在自然界中的發展過程中的應用，例如細胞和植物的生長過程。如果你是進化計算領域的新手、工程師、程序員，甚至是想學習如何模擬植物的進化和共進化的生物學家，本書將為你提供一個視覺豐富且引人入勝的複雜主題介紹。

特點：
- 介紹生物進化的主要機制。
- 通過簡單而具有說明性的例子展示了進化在自然界中的許多迷人方面。
- 解釋了進化計算的每個主要分支：遺傳算法、遺傳編程、進化編程和進化策略。
- 使用作者設計的遺傳編程系統Evolvica，詳細說明了如何通過進化原則編程計算機。
- 詳細展示了如何通過細胞自動機和Lindenmayer系統進化發展性程序。
- 在網上提供了包含本書中所有程序以及支持動畫、電影和圖形的Mathematica筆記本。

作者：
Christian Jacob是加拿大卡爾加里大學計算機科學系的助理教授。他的研究興趣包括進化算法、Lindenmayer系統、生態系統建模、分布式計算、替代編程範式、生物計算和生物信息學。他是本書的德文版《Principia Evolvica Simulierte Evolution mit Mathematica》的作者，該書由dpunkt.verlag出版。

目錄：
- 第1部分：迷人的進化
- 第2部分：進化計算
- 第3部分：如果達爾文是一個程序員
- 第4部分：發展性程序的進化

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