Creative Evolutionary Systems (Hardcover)

David W. Corne, Peter J. Bentley

  • 出版商: Morgan Kaufmann
  • 出版日期: 2001-07-30
  • 售價: $2,450
  • 貴賓價: 9.5$2,328
  • 語言: 英文
  • 頁數: 576
  • 裝訂: Hardcover
  • ISBN: 1558606734
  • ISBN-13: 9781558606739
  • 相關分類: 人工智慧程式語言
  • 立即出貨 (庫存=1)



The use of evolution for creative problem solving is one of the most exciting and potentially significant areas in computer science today. Evolutionary computation is a way of solving problems, or generating designs, using mechanisms derived from natural evolution. This book concentrates on applying important ideas in evolutionary computation to creative areas, such as art, music, architecture, and design. It shows how human interaction, new representations, and approaches such as open-ended evolution can extend the capabilities of evolutionary computation from optimization of existing solutions to innovation and the generation of entirely new and original solutions.

This book takes a fresh look at creativity, exploring what it is and how the actions of evolution can resemble it. Examples of novel evolved solutions are presented in a variety of creative disciplines. The editors have compiled contributions by leading researchers in each discipline.

If you are a savvy and curious computing professional, a computer-literate artist, musician or designer, or a specialist in evolutionary computation and its applications, you will find this a fascinating survey of the most interesting work being done in the area today



An Introduction to Creative Evolutionary Systems

By Peter J. Bentley and David W. Corne


    AI and Creativity

    Evolutionary Computation

    Creative Evolutionary Systems

    Is Evolution Creative?


PART I - Evolutionary Creativity


Chapter 1 - Creativity in Evolution: Individuals, Interactions, and Environments

By Tim Taylor

    1.1 Introduction

    1.2 Creativity and Opened-Ended Evolution

    1.3 Design Issues
      1.3.1 Von Neumann’s Architecture for Self-Reproduction

      1.3.2 Tierra

      1.3.3 Implicit versus Explicit Encoding

      1.3.4 Ability to Perform Other Tasks

      1.3.5 Embeddedness in the Arena of Competition and Richness of Interactions

      1.3.6 Materiality

    1.4 A Full Specification For An Open-Ended Evolutionary Process
      1.4.1 Waddington’s Paradigm for an Evolutionary Process

    1.5 Conclusions




Chapter 2 - Recognizability of the Idea: The Evolutionary Process of Argenia

By Celestino Soddu

    2.1 Introduction

    2.2 Recognizability, Identity, And Complexity

    2.3 Evolutionary Codes: Artificial DNA

    2.4 Natural/Artificial Complexity

    2.5 Giotto, A Medieval Idea In Evolution

    2.6 Rome, Future Scenarios

    2.7 Basilica, Generative Software To Design Complexity

    2.8 Madrid and Milan, Generated Architecture

    2.9 Argenìa, The Natural Industrial Object, And The Artificial Uniqueness Of Species

    2.10 Argenìc Art: Picasso

    2.11 Conclusions



Chapter 3 - Breeding Aesthetic Objects: Art and Artificial Evolution

By Mitchell Whitelaw

    3.1 Introduction

    3.2 Breeding Aesthetic Objects
      3.2.1 A Case Study—Steven Rooke

    3.3 Breeding and Creation
      3.3.1 Creative Agency and the Breeding Process

      3.3.2 The Evolved Aesthetic Object

    3.4 Limits

    3.5 Driessens and Verstappen—An Alternative Approach

    3.6 Conclusions



Chapter 4 - The Beer Can Theory of Creativity

By Liane Gabora

    4.1 Introduction

    4.2 Culture As An Evolutionary Process
      4.2.1 Variation and Convergence in Biology and Culture

      4.2.2 Is More Than One Mind Necessary for Ideas to Evolve?

      4.2.3 Meme and Variations: A Computer Model of Cultural Evolution

      4.2.4 Breadth-First versus Depth-First Exploration

      4.2.5 Dampening Arbitrary Associations and Forging Meaningful Ones

    4.3 Creativity as The Origin Of Culture
      4.3.1 Theoretical Evidence

      4.3.2 Archeological Evidence

      4.3.3 Evidence from Animal Behavior

    4.4 What Caused the Onset of Creativity?

    4.5 Conclusions




PART II Evolutionary Music


Chapter 5 - GenJam: Evolution of a Jazz Improviser

By John A. Biles

    5.1 Introduction

    5.2 Overview and Architecture

    5.3 Representations

    5.4 Genetic Operators and Training
      5.4.1 Crossover

      5.4.2 Musically Meaningful Mutation

    5.5 Real-Time Interaction

    5.6 Conclusions



Chapter 6 - On the Origins and Evolution of Music in Virtual Worlds

By Eduardo Reck Miranda

    6.1 Introduction

    6.2 Evolutionary Modeling
      6.2.1 Transformation and Selection

      6.2.2 Coevolution

      6.2.3 Self-organization

      6.2.4 Level Formation

    6.3 Evolving Sound With Cellular Automata
      6.3.1 The Basics of Cellular Automata

      6.3.2 The Cellular Automaton Used in Our System

      6.3.3 The Synthesis Engine

    6.4 Commentary On The Results

    6.5 Conclusions




Chapter 7 - Vox Populi: Evolutionary Computation for Music Evolution

By Artemis Moroni, Jônatas Manzolli, Fernando Von Zuben, and Ricardo Gudwin

    7.1 Introduction

    7.2 Sound Attributes

    7.3 Evolutionary Musical Cycle
      7.3.1 The Voices Population

      7.3.2 The Rhythm of the Evolution

    7.4 Fitness Evaluation
      7.4.1 The Consonance Criterion

      7.4.2 Melodic Fitness

      7.4.3 Harmonic Fitness

      7.4.4 Voice Range Criterion

      7.4.5 Musical Fitness

    7.5 Interface And Parameter Control

    7.6 Experiments

    7.7 Conclusions




Chapter 8 - The Sound Gallery—An Interactive A-Life Artwork

By Sam Woolf and Adrian Thompson

    8.1 Introduction

    8.2 Evolvable Hardware
      8.2.1 Reconfigurable Chips

    8.3 Gallery Setup
      8.3.1 Setting

      8.3.2 Sensing Systems

    8.4 Contextualization: Artificial Life and Art
      8.4.1 Evolutionary Algorithms and Visual Arts

      8.4.2 Evolutionary Algorithms and Music

      8.4.3 Interactive Genetic Art

      8.4.4 Interactive, Adaptive, and Autonomous (Nongenetic) Artworks

    8.5 The Sound Gallery Algorithms
      8.5.1 Two-Phase Hill-Climbing/ Island Model GA

      8.5.2 Hill-climbing Phase

      8.5.3 Island Model Genetic Algorithm Phase

      8.5.4 The Need for Aging

      8.5.5 Encoding Scheme

      8.5.6 The Fitness Function

      8.5.7 galSim

    8.6 The Experiment
      8.6.1 Results

    8.7 Conclusions





PART III Creative Evolutionary Design


Chapter 9 - Creative Design and the Generative Evolutionary Paradigm

By John Frazer

    9.1 Introduction

    9.2 The Adaptive Model From Nature

    9.3 The Generative Evolutionary Paradigm

    9.4 Problems With The Paradigm

    9.5 Concept Seeding Approach

    9.6 The Reptile Demonstration

    9.7 Universal State Space Modeler

    9.8 Logic Fields

    9.9 Returning to the Analogy with Nature

    9.10 Conclusions



Chapter 10 - Genetic Programming: Biologically Inspired
Computation That Exhibits Creativity in Producing
Human-Competitive Results

By John R. Koza, Forrest H. Bennett III, David Andre, and
Martin A. Keane

    10.1 Introduction

    10.2 Inventiveness And Creativity

    10.3 Genetic Programming

    10.4 Applying Genetic Programming To Circuit Synthesis
      10.4.1 Campbell 1917 Ladder Filter Patent

      10.4.2 Zobel 1925 "M-Derived Half Section" Patent

      10.4.3 Cauer 1934–1936 Elliptic Filter Patents

      10.4.4 Amplifier, Computational, Temperature-Sensing, Voltage Reference, and
      Other Circuits

    10.5 Topology, Sizing, Placement, and Routing Of Circuits Contents

    10.6 Automatic Synthesis Of Controllers By Means Of Genetic Programming
      10.6.1 Robust Controller for a Two-Lag Plant

    10.7 The Illogical Nature Of Creativity And Evolution

    10.8 Conclusions



Chapeter 11 - Toward a Symbiotic Coevolutionary Approach to Architecture

By Helen Jackson

    11.1 Introduction

    11.2 Lindenmayer Systems
      11.2.1 Example L-Systems

      11.2.2 The Isospatial Grid

      11.2.3 Spatial Embryology

    11.3 Artificial Selection
      11.3.1 The Eyeball Test

    11.4 Single-Goal Evolution
      11.4.1 "Generic Function" as Fitness Function

      11.4.2 Evolution toward Low i-Values

      11.4.3 Structural Stability

      11.4.4 Architecture As a Multigoal Task

      11.4.5 Dual-Goal Evolution

    11.5 Representation, Systems, And Symbiosis
      11.5.1 Coevolution

      11.5.2 Naïve Architectural Form Representation

      11.5.3 Spatial Embryology

    11.6 Conclusions




Chapter 12 - Using Evolutionary Algorithms to Aid Designers of Architectural Structures

By Peter von Buelow

    12.1 Introduction

    12.2 Analysis Tools Vs. Design Tools

    12.3 Advantages Of Evolutionary Systems In Design Contents
      12.3.1 Use of Populations

      12.3.2 Recombination and Mutation

      12.3.3 Wide Search of Design Space

      12.3.4 No Knowledge of the Objective Function

      12.3.5 Imitation of Human Design Process

      12.3.6 Can Learn from Designer

    12.4 Characteristics of an IGDT
      12.4.1 Definition of the IGDT Concept

      12.4.2 Relation of IGDT to Design Process

    12.5 Mechanics of an IGDT

    12.6 IGDT Operation
      12.6.1 Problem Definition

      12.6.2 Initial IGDT Generation

      12.6.3 Initial Generation with Designer Selection/Interaction

      12.6.4 Second-Generation IGDT Response

      12.6.5 Second-Generation Designer Interaction

      12.6.6 Third Generation

    12.7 Conclusions




PART IV Evolutionary Art


Chapter 13 - Eons of Genetically Evolved Algorithmic Images

By Steven Rooke

    13.1 Introduction

    13.2 Using GP for Art
      13.2.1 Genetic Variation

      13.2.2 Genetic Library

      13.2.3 Functions and Node Internals

      13.2.4 A Typical Run

    13.3 Horizon Lines And Fantasy Landscapes

    13.4 Genetic Fractals
      13.4.1 Second-Order Subtleties of Orbit Trajectories during Iteration in the Complex Plane

    13.5 The Genetic Cross Dissolve

    13.6 What Is It?
      13.6.1 Constraints of Color and Form

      13.6.2 A Joyride for the Visual Cortex?

      13.6.3 Approaching the Organic

    13.7 Conclusions



Chapter 14 - Art, Robots, and Evolution as a Tool for Creativity

By Luigi Pagliarini and Henrik Hautop Lund

    14.1 Introduction

    14.2 The Social Context Of Electronics
      14.2.1 Where Electronics Acts

      14.2.2 How Technology Influences Art (the World)

      14.2.3 How Technology Gets Feedback (from Art and the World)

    14.3 What Artist?
      14.3.1 Two Different Concepts or Aspects of the Artist

      14.3.2 Art and Human Language: The "Immaterial" Artist

      14.3.3 Art and Human Technique: The "Material" Artist

    14.4 Electronic Art
      14.4.1 A New Electronic Space

      14.4.2 The "Material" Electronic Artist

      14.4.3 The "Immaterial" Artist and the Uses of Electronics

      14.4.4 Example—The Artificial Painter

    14.5 Alive Art
      14.5.1 Other Artistic Movements Based on Electronics

      14.5.2 Alive Art

      14.5.3 The Aliver

      14.5.4 The "Alive Art Effect"

      14.5.5 Example—LEGO Robot Artists

    14.6 Conclusions



Chapter 15 - Stepping Stones in the Mist

By Paul Brown

    15.1 Introduction

    15.2 On My Approach as an Artist—A Disclaimer

    15.3 Major Influences

    15.4 Historical Work—1960s and 1970s

    15.5 Early Computer Work

    15.6 Recent Work

    15.7 Current And Future Directions

    15.8 Conclusions




Chapter 16 - Evolutionary Generation of Faces 409

By Peter J. B. Hancock and Charlie D. Frowd

    16.1 Introduction
      16.1.1 Eigenfaces

      16.1.2 Evolutionary Face Generator System

    16.2 Testing
      16.2.1 Apparatus

      16.2.2 Generation of Face Images

      16.2.3 Evolutionary Algorithm

      16.2.4 Participants

    16.3 Results

    16.4 Discussion

    16.5 Conclusions




Chapter 17 - The Escher Evolver: Evolution to the People

By A. E. Eiben, R. Nabuurs, and I. Booij

    17.1 Introduction

    17.2 The Mathematical System Behind Escher’s Tiling

    17.3 Evolutionary Algorithm Design
      17.3.1 Representation

      17.3.2 Ground Shape and Transformation System

      17.3.3 Genetic Operators: Mutation and Crossover

      17.3.4 Selection Mechanism

    17.4 Implementation and The Working of The System
      17.4.1 Stand-Alone Version

      17.4.2 First Networked Version

      17.4.3 Second Networked Version

    17.5 Conclusions




PART V Evolutionary Innovation


Chapter 18 - The Genetic Algorithm as a Discovery Engine: Strange
Circuits and New Principles

By Julian F. Miller, Tatiana Kalganova, Natalia Lipnitskaya, and Dominic Job

    18.1 Introduction

    18.2 The Space of All Representations

    18.3 Evolutionary Algorithms That Assemble Electronic Circuits From A
    Collection of Available Components
      18.3.1 Binary Circuit Symbols

      18.3.2 Multiple-Valued Circuits

    18.4 Results
      18.4.1 One-Bit Adder

      18.4.2 Two-Bit Adder

      18.4.3 Two-Bit Multiplier

      18.4.4 Three-Bit Multiplier

      18.4.5 Multiple-Valued One-Digit Adder with Carry

    18.5 Fingerprinting and Principle Extraction

    18.6 Conclusions



Chapter 19 - Discovering Novel Fighter Combat Maneuvers:
Simulating Test Pilot Creativity

By R. E. Smith, B. A. Dike, B. Ravichandran, A. El-Fallah, and R. K. Mehra

    19.1 Introduction

    19.2 Fighter Aircraft Maneuvering

    19.3 Genetics-Based Machine Learning
      19.3.1 Learning Classifier Systems

      19.3.2 The LCS Used Here

    19.4 "One-Sided Learning" Results

    19.5 "Two-Sided Learning" Results

    19.6 Differences In Goals And Techniques

    19.6.1 Implications of This Goal

    19.7 Conclusions




Chapter 20 - Innovative Antenna Design Using Genetic Algorithms

By Derek S. Linden

    20.1 Introduction

    20.2 Antenna Basics

    20.3 Conventional Designs and Unconventional Applications: The Yagi-Uda Antenna

    20.4 Unconventional Designs and Conventional Applications: Crooked-Wire
    And Treelike Genetic Antennas
      20.4.1 The Crooked-Wire Genetic Antenna

      20.4.2 Treelike Genetic Antennas

    20.5 Conclusions



Chapter 21 - Evolutionary Techniques in Physical Robotics

By Jordan B. Pollack, Hod Lipson, Sevan Ficici, Pablo Funes,
Greg Hornby, and Richard A. Watson

    21.1 Introduction

    21.2 Coevolution

    21.3 Research Thrusts

    21.4 Evolution In Simulation

    21.5 Buildable Simulation

    21.6 Evolution and Construction of Electromechanical Systems

    21.7 Embodied Evolution

    21.8 Conclusions




Chapter 22 - Patenting of Novel Molecules Designed via Evolutionary Search

By Shail Patel, Ian Stott, Manmohan Bhakoo, and Peter Elliott

    22.1 Introduction

    22.2 Design Cycle

    22.3 Hypothesis: Mechanism Of Action

    22.4 Experimental Measures And Modeling Techniques
      22.4.1 Molecular Modeling

      22.4.2 Neural Networks

    22.5 Evolution

    22.6 Patent Application
      22.6.1 Comparing Patent Spaces

    22.7 Conclusions







創意演化系統簡介 - Peter J. Bentley和David W. Corne
第一部分 - 演化創造力
第1章 - 演化中的創造力:個體、互動和環境 - Tim Taylor
第2章 - 概念的可識別性:Argenia的演化過程 - Celestino Soddu
第3章 - 繁殖美學物體:藝術和人工演化 - Mitchell Whitelaw
第4章 - 創造力的啤酒罐理論 - Liane Gabora