McCormack / d'Inverno / d’Inverno Computers and Creativity

1. Auflage 2012
ISBN: 978-3-642-31727-9
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 441 Seiten

This interdisciplinary volume introduces new theories and ideas on creativity from the perspectives of science and art. Featuring contributions from leading researchers, theorists and artists working in artificial intelligence, generative art, creative computing, music composition, and cybernetics, the book examines the relationship between computation and creativity from both analytic and practical perspectives. Each contributor describes innovative new ways creativity can be understood through, and inspired by, computers.The book tackles critical philosophical questions and discusses the major issues raised by computational creativity, including: whether a computer can exhibit creativity independently of its creator; what kinds of creativity are possible in light of our knowledge from computational simulation, artificial intelligence, evolutionary theory and information theory; and whether we can begin to automate the evaluation of aesthetics and creativity in silico. These important, often controversial questions are contextualised by current thinking in computational creative arts practice. Leading artistic practitioners discuss their approaches to working creatively with computational systems in a diverse array of media, including music, sound art, visual art, and interactivity.The volume also includes a comprehensive review of computational aesthetic evaluation and judgement research, alongside discussion and insights from pioneering artists working with computation as a creative medium over the last fifty years. A distinguishing feature of this volume is that it explains and grounds new theoretical ideas on creativity through practical applications and creative practice.Computers and Creativity will appeal to theorists, researchers in artificial intelligence, generative and evolutionary computing, practicing artists and musicians, students and any reader generally interested in understanding how computers can impact upon creativity. It bridges concepts from computer science, psychology, neuroscience, visual art, music and philosophy in an accessible way, illustrating how computers are fundamentally changing what we can imagine and create, and how we might shape the creativity of the future.Computers and Creativity will appeal to theorists, researchers in artificial intelligence, generative and evolutionary computing, practicing artists and musicians, students and any reader generally interested in understanding how computers can impact upon creativity. It bridges concepts from computer science, psychology, neuroscience, visual art, music and philosophy in an accessible way, illustrating how computers are fundamentally changing what we can imagine and create, and how we might shape the creativity of the future.

Jon McCormack is an electronic media artist and researcher in computing. He holds a degree in Applied Mathematics and Computer Science from Monash University, a Graduate Diploma of Art (Film and Television) from Swinburne University and a PhD in Computer Science from Monash University, Melbourne. He is currently Associate Professor in Computer Science, an ARC Australian Research Fellow and director of the Centre for Electronic Media Art (CEMA) at Monash University. His research spans generative art and design, evolutionary systems, creativity, visualisation, interaction, machine learning, L-systems and developmental models. His artworks have been widely exhibited at leading galleries, museums and symposia, including the Museum of Modern Art (New York, USA), Tate Gallery (Liverpool, UK), ACM SIGGRAPH (USA), Prix Ars Electronica (Austria) and the Australian Centre for the Moving Image (Australia). He is the recipient of 16 awards for new media art and research including prizes at Ars Electronica (Austria), Images du Futur (Canada), New Voices, New Visions (USA), Alias/Wavefront (USA), The John Lansdown Award for Interactive Media (Europe/UK), and Nagoya Biennial (Japan). Mark d'Inverno holds an MA and MSc in Mathematics from Oxford University and a PhD from University College London in Artificial Intelligence. He is Professor of Computer Science at Goldsmiths, University of London and for four years between 2007 and 2011 was head of the Department of Computing which has championed interdisciplinary research and teaching around computers and creativity for nearly a decade. He has published over 100 articles including books, journal and conference articles and led research projects in a diverse range of fields relating to computer science including multi-agent systems, systems biology, art, music and social media. During the final editing of this book he took a research sabbatical shared between the Artificial Intelligence Research Institute and the Sony Computer Science Laboratory in Paris. He is currently the principal investigator or co-investigator  on a range of EU and UK projects spanning community building, sharing social experiences, inspiring creativity, cultural engagement and music education. He is a critically acclaimed jazz pianist and composer and over the last 25 years has led a variety of successful bands in a range of different musical genres.

Autoren/Hrsg.

McCormack, Jon

d’Inverno, Mark

D'Inverno, Mark

Inhaltsverzeichnis

1;Computers and Creativity;3
1.1;Foreword;5
1.2;Preface;7
1.2.1;Why Does Computing Matter to Creativity?;7
1.2.2;Summary of Contributions;9
1.3;Acknowledgements;14
1.4;Contents;15
1.5;Contributors;17
2;Part I: Art;23
2.1;Chapter 1: The Painting Fool: Stories from Building an Automated Painter;24
2.1.1;1.1 Introduction;24
2.1.2;1.2 The Painting Fool in Context;27
2.1.3;1.3 Guiding Principles;32
2.1.3.1;1.3.1 Ever-Decreasing Circles;32
2.1.3.2;1.3.2 Paradigms Lost;32
2.1.3.3;1.3.3 The Whole Is More Than a Sum of the Parts;33
2.1.3.4;1.3.4 Climbing the Meta-mountain;33
2.1.3.5;1.3.5 The Creativity Tripod;34
2.1.3.6;1.3.6 Beauty Is in the Mind of the Beholder;35
2.1.3.7;1.3.7 Good Art Changes Your Mind;36
2.1.4;1.4 Illustrative Projects;37
2.1.4.1;1.4.1 Non-photorealistic Rendering;38
2.1.4.2;1.4.2 Emotional Modelling;41
2.1.4.3;1.4.3 Scene Construction;45
2.1.4.4;1.4.4 Collage Generation;50
2.1.4.5;1.4.5 Paint Dances;52
2.1.5;1.5 Future Directions;53
2.1.6;1.6 Conclusions;56
2.1.7;References;57
2.2;Chapter 2: Creative Ecosystems;60
2.2.1;2.1 Creative Systems;60
2.2.1.1;2.1.1 Spaces of Possibility;62
2.2.2;2.2 Evolutionary Computing and Creativity;64
2.2.3;2.3 Ecosystems;66
2.2.3.1;2.3.1 Biological Ecosystems;67
2.2.3.2;2.3.2 Ecosystem Models in the Creative Arts;68
2.2.3.2.1;Design and Architecture.;68
2.2.3.2.2;Music and Performance.;69
2.2.3.2.3;Visual and Installation Art.;69
2.2.4;2.4 Ecosystem Design Patterns;72
2.2.4.1;2.4.1 Environments: Conditions and Resources;72
2.2.4.2;2.4.2 Self-observation and Feedback;73
2.2.4.3;2.4.3 Automation and the Creative Role of the Artist;76
2.2.5;2.5 Conclusions;78
2.2.6;References;79
2.3;Chapter 3: Construction and Intuition: Creativity in Early Computer Art;82
2.3.1;3.1 Introduction;82
2.3.2;3.2 The First Narration: On Random Polygons;85
2.3.2.1;3.2.1 Georg Nees;90
2.3.2.2;3.2.2 A. Michael Noll;92
2.3.2.3;3.2.3 Frieder Nake;92
2.3.3;3.3 The Second Narration: On Three Artists;95
2.3.3.1;3.3.1 Vera Molnar;97
2.3.3.2;3.3.2 Charles Csuri;98
2.3.3.3;3.3.3 Manfred Mohr;100
2.3.4;3.4 The Third Narration: On Two Programs;102
2.3.4.1;3.4.1 Harold Cohen: AARON;104
2.3.4.2;3.4.2 Frieder Nake: Generative Aesthetics I;107
2.3.5;3.5 The Fourth and Last Narration: On Creativity;111
2.3.6;3.6 Conclusion;112
2.3.7;References;114
2.4;Chapter 4: Evaluation of Creative Aesthetics;116
2.4.1;4.1 Introduction;117
2.4.2;4.2 Background: Evaluation of Artistic Artefacts;117
2.4.3;4.3 A Conversation on Evaluation;119
2.4.4;4.4 Conclusion;132
2.4.5;References;132
3;Part II: Music;133
3.1;Chapter 5: Musical Virtuosity and Creativity;134
3.1.1;5.1 Virtuosos as Exceptional Humans;134
3.1.1.1;5.1.1 Virtuosity in Art;134
3.1.1.2;5.1.2 The Cognitive Science Perspective on Virtuosity;136
3.1.1.3;5.1.3 Virtuosity as an Attraction Device;136
3.1.1.4;5.1.4 Virtuosos as Creators;137
3.1.2;5.2 The Case of Jazz;138
3.1.2.1;5.2.1 The Rules of the Game;139
3.1.2.2;5.2.2 Bebop Phrases;139
3.1.2.3;5.2.3 The Melodic/Harmonic Interplay;140
3.1.2.3.1;5.2.3.1 Harmonic Consistency;140
3.1.2.3.2;5.2.3.2 Continuity;141
3.1.2.3.2.1;The One-Step-Max Theorem;141
3.1.2.4;5.2.4 Playing Outside and Side-Slipping;141
3.1.2.5;5.2.5 Virtuosity Is to Improvisation as Running Is to Walking;143
3.1.2.6;5.2.6 Claims;144
3.1.3;5.3 Modelling Jazz Improvisation Generation;145
3.1.3.1;5.3.1 Non-Markovian Approaches;145
3.1.3.2;5.3.2 Markov Chain Approaches;146
3.1.4;5.4 A Note-Based Jazz Generator;148
3.1.4.1;5.4.1 Pitches for Representation, Beats for Generation;148
3.1.4.2;5.4.2 Handling Harmony;149
3.1.4.3;5.4.3 Chord Change Negotiation;151
3.1.4.4;5.4.4 An Example Training Set;152
3.1.5;5.5 Escaping Markovian Boredom;155
3.1.5.1;5.5.1 Side-Slips and Formal Transforms;155
3.1.5.2;5.5.2 The Control Issue;157
3.1.5.3;5.5.3 Reusing Intentional Scores;159
3.1.6;5.6 Virtuoso: A Virtuoso Enabling Interactive System;161
3.1.7;5.7 Discussion;162
3.1.8;References;163
3.2;Chapter 6: Live Algorithms: Towards Autonomous Computer Improvisers;166
3.2.1;6.1 Introduction;166
3.2.2;6.2 The Field: Creative Group Improvisation;168
3.2.2.1;6.2.1 Collective Improvisation;168
3.2.2.2;6.2.2 The Individual (Human or Machine) in Interaction;168
3.2.2.2.1;6.2.2.1 Autonomy;168
3.2.2.2.2;6.2.2.2 Novelty;169
3.2.2.2.3;6.2.2.3 Participation;169
3.2.2.2.4;6.2.2.4 Leadership;170
3.2.2.3;6.2.3 Relationship of the Four Attributes to Creativity;170
3.2.3;6.3 Theoretical Considerations;171
3.2.3.1;6.3.1 P, Q and f;171
3.2.3.2;6.3.2 De?nition of a Live Algorithm;171
3.2.3.3;6.3.3 Architecture;171
3.2.3.4;6.3.4 The Live Algorithm from the Outside;175
3.2.3.5;6.3.5 Arti?cial Intelligence;178
3.2.4;6.4 Live Algorithms in Context;180
3.2.4.1;6.4.1 Live Algorithm Behaviour;180
3.2.4.1.1;6.4.1.1 Shadowing;180
3.2.4.1.2;6.4.1.2 Mirroring;181
3.2.4.1.3;6.4.1.3 Coupling;181
3.2.4.1.4;6.4.1.4 Negotiation;182
3.2.4.2;6.4.2 Agency and Live Algorithms;183
3.2.4.3;6.4.3 Live Algorithms as Musicians;185
3.2.5;6.5 Prototypes;186
3.2.6;6.6 Further Considerations;189
3.2.6.1;6.6.1 Embodiment;189
3.2.6.2;6.6.2 Learning;190
3.2.6.3;6.6.3 Anticipated Criticisms;190
3.2.6.4;6.6.4 Cultural Embeddedness;191
3.2.6.5;6.6.5 A Final Note;191
3.2.7;References;192
3.3;Chapter 7: The Extended Composer;194
3.3.1;7.1 Introduction;194
3.3.1.1;7.1.1 Thinking Through Tools;195
3.3.1.2;7.1.2 The Computer as Meta-tool;197
3.3.1.3;7.1.3 Digital Partners in Creative Practice;197
3.3.2;7.2 Computational Aides for Algorithmic Inspiration;199
3.3.2.1;7.2.1 Computational Strategies and Algorithmic Aides;200
3.3.3;7.3 The Human-Computer Partnership: Characteristics and Categories;201
3.3.3.1;7.3.1 Feedback;202
3.3.3.2;7.3.2 Exploration;204
3.3.3.3;7.3.3 Intimacy;207
3.3.3.4;7.3.4 Interactivity;208
3.3.3.5;7.3.5 Introspection;210
3.3.3.6;7.3.6 Time;212
3.3.3.7;7.3.7 Authorship;214
3.3.3.7.1;The "Inhuman" Argument;214
3.3.3.7.2;The "Invisible Hand" Argument;215
3.3.3.7.3;The "Creative Vitalism" Argument;215
3.3.3.8;7.3.8 Value;216
3.3.4;7.4 In Summary;217
3.3.4.1;7.4.1 Future Explorations;218
3.3.4.2;7.4.2 Final Re?ections;219
3.3.5;References;219
3.4;Chapter 8: Between Material and Ideas: A Process-Based Spatial Model of Artistic Creativity;223
3.4.1;8.1 Introduction;223
3.4.1.1;8.1.1 Background;224
3.4.1.2;8.1.2 Outline;226
3.4.2;8.2 Tools;226
3.4.3;8.3 The Model;228
3.4.3.1;8.3.1 Material Space and Representation;229
3.4.3.2;8.3.2 The Conceptual Representation;233
3.4.3.3;8.3.3 Interplay Between Representations;234
3.4.3.4;8.3.4 Example Scenarios;235
3.4.3.5;8.3.5 Appreciation and Novelty;237
3.4.3.6;8.3.6 The Model in Context;238
3.4.3.7;8.3.7 Craft and Skill;240
3.4.3.8;8.3.8 New Tools and Tool Design;241
3.4.3.9;8.3.9 Social and Cultural Creativity;242
3.4.3.10;8.3.10 Abstraction Levels;242
3.4.4;8.4 Implications for Computational Creativity;243
3.4.4.1;8.4.1 Implementation of the Model;244
3.4.4.2;8.4.2 Conceptual Representations;245
3.4.4.3;8.4.3 Re-conceptualisation;246
3.4.4.4;8.4.4 Memory and Learning;247
3.4.5;8.5 Final Remarks;248
3.4.6;References;249
3.5;Chapter 9: Computer Programming in the Creative Arts;252
3.5.1;9.1 Introduction;252
3.5.2;9.2 Creative Processes;255
3.5.2.1;9.2.1 Creative Process of Bricolage;256
3.5.3;9.3 Anthropomorphism and Metaphor in Programming;257
3.5.4;9.4 Symbols and Space;259
3.5.5;9.5 Components of Creativity;263
3.5.6;9.6 Programming in Time;265
3.5.6.1;9.6.1 Interactive Programming;266
3.5.7;9.7 Conclusion;267
3.5.8;References;268
4;Part III: Theory;270
4.1;Chapter 10: Computational Aesthetic Evaluation: Past and Future;271
4.1.1;10.1 Introduction;271
4.1.1.1;10.1.1 What Do We Mean by Computational Aesthetic Evaluation?;272
4.1.1.2;10.1.2 Why Is Computational Aesthetic Evaluation so Dif?cult if not Impossible?;273
4.1.2;10.2 A Brief History of Computational Aesthetic Evaluation;273
4.1.2.1;10.2.1 Formulaic and Geometric Theories;274
4.1.2.2;10.2.2 Design Principles;276
4.1.2.3;10.2.3 Arti?cial Neural Networks and Connectionist Models;277
4.1.2.4;10.2.4 Evolutionary Systems;278
4.1.2.5;10.2.5 Interactive Evolutionary Computation;279
4.1.2.6;10.2.6 Automated Fitness Functions Based on Performance Goals;280
4.1.2.7;10.2.7 Evolutionary Fitness Measured as Error Relative to Exemplars;282
4.1.2.8;10.2.8 Automated Fitness Functions Based on Complexity Measures;283
4.1.2.9;10.2.9 Automated Fitness Functions in Evolutionary Music Systems;283
4.1.2.10;10.2.10 Multi-objective Aesthetic Fitness Functions in Evolutionary Systems;284
4.1.2.11;10.2.11 Biologically Inspired Extensions to Simple Evolutionary Computation;285
4.1.2.11.1;10.2.11.1 Coevolution;286
4.1.2.11.2;10.2.11.2 Niche Construction by Agents;287
4.1.2.11.3;10.2.11.3 Agent Swarm Behaviour;288
4.1.2.11.4;10.2.11.4 Curious Agents;289
4.1.2.11.5;10.2.11.5 Human Aesthetics, Meta-aesthetics, and Alternatives to Fitness Functions;290
4.1.2.12;10.2.12 Complexity Based Models of Aesthetics;290
4.1.3;10.3 The Future of Computational Aesthetic Evaluation;293
4.1.3.1;10.3.1 The Origins of Art and the Art Instinct;293
4.1.3.2;10.3.2 Psychological Models of Human Aesthetics;295
4.1.3.2.1;10.3.2.1 Arnheim-Gestalt and Aesthetics;295
4.1.3.2.2;10.3.2.2 Berlyne-Arousal Potential and Preferences;295
4.1.3.2.3;10.3.2.3 Martindale-Prototypicality and Neural Networks;297
4.1.3.3;10.3.3 Empirical Studies of Human Aesthetics;299
4.1.3.4;10.3.4 Neuroaesthetics;300
4.1.3.5;10.3.5 Computing Inspired by Neurology;300
4.1.3.6;10.3.6 The Neocortex and Hierarchical Temporal Memory;301
4.1.3.7;10.3.7 Computer Architectures for Evolvable Hardware;302
4.1.4;10.4 Conclusion;302
4.1.5;References;303
4.2;Chapter 11: Computing Aesthetics with Image Judgement Systems;310
4.2.1;11.1 Introduction;310
4.2.2;11.2 Validation Approaches for AJS;314
4.2.2.1;11.2.1 Psychological Tests;314
4.2.2.2;11.2.2 User Evaluation and Popularity Prediction;317
4.2.2.3;11.2.3 Style and Author Classi?cation;320
4.2.3;11.3 The Evolution of an AJS;322
4.2.3.1;11.3.1 A Heuristic AJS;322
4.2.3.2;11.3.2 Learning AJSs;324
4.2.3.2.1;11.3.2.1 Feature Extraction;325
4.2.3.2.1.1;Pre-processing;325
4.2.3.2.1.2;Metrics Application;326
4.2.3.2.1.3;Feature Building;327
4.2.3.2.2;11.3.2.2 DJT Experiments;327
4.2.3.2.3;11.3.2.3 Author Identi?cation Experiments;328
4.2.3.2.4;11.3.2.4 Image Classi?cation Based on Online Evaluation;330
4.2.3.2.5;11.3.2.5 Integration in an Image Generation System;330
4.2.4;11.4 Conclusions;332
4.2.5;References;333
4.3;Chapter 12: A Formal Theory of Creativity to Model the Creation of Art;338
4.3.1;12.1 The Basic Idea;338
4.3.2;12.2 Relation to Previous, Less Formal Work;339
4.3.3;12.3 Formal Details;341
4.3.3.1;12.3.1 Continuous Time Formulation;344
4.3.4;12.4 Previous Approximative Implementations of the Theory;345
4.3.5;12.5 Aesthetic Reward = Change of Subjective Compressibility?;347
4.3.6;12.6 Low-Complexity Art as End Product of a Search Process Modelled by the Formal Theory of Creativity;348
4.3.7;12.7 Conclusion;349
4.3.8;References;349
4.4;Chapter 13: Creativity Re?ned: Bypassing the Gatekeepers of Appropriateness and Value;353
4.4.1;13.1 Introduction;353
4.4.2;13.2 What Is Creativity?;355
4.4.3;13.3 De?ning Creativity;357
4.4.3.1;13.3.1 Methods for Discovering Novel Representations;359
4.4.3.2;13.3.2 Objective Versus Psychological Creativity;360
4.4.4;13.4 Objections and Replies;361
4.4.4.1;13.4.1 The Failure of Randomness;361
4.4.4.2;13.4.2 The Verstehen Objection;362
4.4.4.3;13.4.3 The Very Possibility of Creativity;363
4.4.5;13.5 Consequences;363
4.4.5.1;13.5.1 The Irrelevance of Value;363
4.4.5.2;13.5.2 The Irrelevance of Appropriateness;364
4.4.5.3;13.5.3 Inferring Frameworks from Patterns;364
4.4.5.4;13.5.4 Creativity Viewed as Compression;364
4.4.5.5;13.5.5 Degrees of Creativity;365
4.4.6;13.6 Examples: Creativity in Human Endeavour;365
4.4.6.1;Number Theory.;365
4.4.6.2;Visual Arts.;365
4.4.7;13.7 Examples: Creativity in Nature;366
4.4.7.1;From Physics and Chemistry to Evolutionary Biology.;366
4.4.7.2;Ecosystems.;366
4.4.7.3;Dancing Bowerbirds, Painting Elephants and Primate Typists.;367
4.4.8;13.8 Realising Our De?nition of Creativity in Software;368
4.4.8.1;13.8.1 The Automatic Generation of Creative Biomorphs;368
4.4.8.2;13.8.2 Testing Creative Software Against Human Concepts of Creativity;370
4.4.9;13.9 Discussion;371
4.4.10;13.10 Conclusions;372
4.4.11;References;373
4.5;Chapter 14: Generative and Adaptive Creativity: A Uni?ed Approach to Creativity in Nature, Humans and Machines;375
4.5.1;14.1 Questions About Creativity;375
4.5.2;14.2 Generative and Adaptive Creativity;377
4.5.3;14.3 Generative and Adaptive Creativity in the Arts, in Humans, Human Groups and in Silico;379
4.5.3.1;14.3.1 The Creativity of Social Systems Is More than the Sum of Individual Creative Acts;380
4.5.3.2;14.3.2 Social Systems Can Exhibit Both Generative and Adaptive Creativity;382
4.5.3.2.1;14.3.2.1 The Causes and Effects of Culture;382
4.5.3.2.2;14.3.2.2 Social Groups as Adaptive Units;383
4.5.3.2.3;14.3.2.3 Social Groups as Non-adaptive Generators;385
4.5.3.2.4;14.3.2.4 Modelling Creativity in Social Systems;386
4.5.3.3;14.3.3 Individual Humans Can Exhibit Generative and Adaptive Creativity;387
4.5.4;14.4 Generative and Adaptive Approaches to Arts-Based Computational Creativity;388
4.5.4.1;14.4.1 Generative Creative Systems Can Be Externally Useful;389
4.5.4.2;14.4.2 Adaptive Creative Systems Can Be Useful to Others;390
4.5.5;14.5 Conclusion;392
4.5.6;References;393
4.6;Chapter 15: Creating New Informational Primitives in Minds and Machines;396
4.6.1;15.1 Introduction;396
4.6.2;15.2 Emergence and Creativity;399
4.6.2.1;15.2.1 What Constitutes a New Primitive?;400
4.6.2.2;15.2.2 Primitives and Interpretive Frames;401
4.6.2.3;15.2.3 Novel Combinations of Closed Sets of Primitives;402
4.6.2.4;15.2.4 Limits on Computations on Existing Primitives;403
4.6.2.5;15.2.5 Creation of New Primitives;405
4.6.2.6;15.2.6 Combinatoric and Creative Emergence in Aesthetic Contexts;407
4.6.3;15.3 Creativity in Self-constructing Cybernetic Percept-Action Systems;408
4.6.3.1;15.3.1 A Taxonomy of Adaptive Devices;408
4.6.3.2;15.3.2 Semiotics of Adaptive Devices;410
4.6.3.3;15.3.3 Capabilities and Limitations of Adaptive Devices;411
4.6.3.4;15.3.4 Pask's "Organic Analogues to the Growth of a Concept";413
4.6.3.5;15.3.5 Organisational Closure and Epistemic Autonomy;415
4.6.4;15.4 Recognising Different Types of Creativity;416
4.6.4.1;15.4.1 Emergence-Relative-to-a-Model;416
4.6.4.2;15.4.2 Tracking Emergent Functions in a Device;416
4.6.5;15.5 New Signal Primitives in Neural Systems;418
4.6.5.1;15.5.1 New Primitives in Signalling Networks;419
4.6.5.2;15.5.2 Brains as Networks of Adaptive Pattern-Resonances;420
4.6.5.3;15.5.3 Regenerative Loops;421
4.6.5.4;15.5.4 Multidimensional Signals;423
4.6.5.5;15.5.5 Temporal Coding and Signal Multiplexing;423
4.6.5.6;15.5.6 Emergent Annotative Tags and Their Uses;425
4.6.6;References;427
5;Part IV: Epilogue;431
5.1;Chapter 16: Computers and Creativity: The Road Ahead;432
5.1.1;16.1 Where to From Here?;432
6;Index;436