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The Computational Beauty of Nature (Computer Explorations of Fractals, Chaos, Complex Systems, and Adaptation)

List Price: $65.00
SKU:
9780262561273
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  • Product Details

    Author:
    Gary William Flake
    Format:
    Paperback
    Pages:
    520
    Publisher:
    MIT Press (January 27, 2000)
    Language:
    English
    ISBN-13:
    9780262561273
    ISBN-10:
    0262561271
    Weight:
    31.8oz
    Dimensions:
    8" x 9" x 0.98"
    Case Pack:
    14
    File:
    RandomHouse-PRH_Book_Company_PRH_PRT_Onix_full_active_D20260405T164852_155746773-20260405.xml
    Folder:
    RandomHouse
    List Price:
    $65.00
    As low as:
    $50.05
    Publisher Identifier:
    P-RH
    Discount Code:
    A
    QuickShip:
    Yes
    Audience:
    General/trade
    Country of Origin:
    United States
    Pub Discount:
    65
    Imprint:
    Bradford Books
  • Overview

    Gary William Flake develops in depth the simple idea that recurrent rules can produce rich and complicated behaviors.

    In this book Gary William Flake develops in depth the simple idea that recurrent rules can produce rich and complicated behaviors. Distinguishing "agents" (e.g., molecules, cells, animals, and species) from their interactions (e.g., chemical reactions, immune system responses, sexual reproduction, and evolution), Flake argues that it is the computational properties of interactions that account for much of what we think of as "beautiful" and "interesting." From this basic thesis, Flake explores what he considers to be today's four most interesting computational topics: fractals, chaos, complex systems, and adaptation.

    Each of the book's parts can be read independently, enabling even the casual reader to understand and work with the basic equations and programs. Yet the parts are bound together by the theme of the computer as a laboratory and a metaphor for understanding the universe. The inspired reader will experiment further with the ideas presented to create fractal landscapes, chaotic systems, artificial life forms, genetic algorithms, and artificial neural networks.