BOOK REVIEW

Juan Romero and Penousal Machado (eds): The Artof Artificial Evolution: A Handbook on EvolutionaryArt and Music

Natural Computing Series, Springer Science+Business Media,2008, 460 pp, 169 illustrations, 91 in colour, Hard Cover withDVD, ISBN: 978-3-540-72876-4

Jeroen Eggermont

Published online: 21 October 2008

� Springer Science+Business Media, LLC 2008

The editors’ objective was to create a handbook for evolutionary art and music by

providing extensive coverage of existing work, giving enough background

information for newcomers to get started and to provide possible directions for

research. It contains 19 chapters written by almost 40 authors and is divided into

five parts. The initial chapters introduce visual evolutionary art, while the chapters

of the second part cover evolutionary music. Part three describes applications such

as design tools using evolutionary art, evolving facial composites or reproducing the

work of the Dutch painters Mondriaan and M.C. Escher. The chapters in the fourth

part should appeal more to artists, since they look at evolutionary art more from an

artist’s point of view, rather than that of a computer scientist. The last part poses

challenges for the future.

Although the book contains many interesting chapters with examples of

evolutionary art and music, the two most important chapters for everyone new to

the field are the first and the last.

In the first chapter, Matthew Lewis gives a broad overview (including almost 200

references) of evolutionary art and design. He starts with a brief introduction to

concepts and terminology of evolutionary computation. This is aimed at artists and

other readers outside EC and should help when reading the rest of the book. The

overview of visual art and design is itself divided into three sections. The sections

are based on the dimensionality of the artwork: 2D (e.g. paintings), 3D (e.g. 3D

forms or plants in virtual environments) and 4D (e.g. animated characters in a 3D

environment). In each section a wide range of approaches are discussed, which

shows how broad the field is. At the end of his chapter Lewis discusses some of the

challenges in evolving visual art. This is probably more interesting to computer

scientists than artists. These challenges range from the shape of fitness landscapes,

J. Eggermont (&)

Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden,

The Netherlands

e-mail: J.Eggermont@lumc.nl

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DOI 10.1007/s10710-008-9071-0

to controlling diversity, and to something as practical as strategies to reduce user

fatigue when the user serves as the fitness function.

In the last chapter of the book, Facing the Future, Jon McCormack poses eight

challenges or open problems for the future. One such problem is that of fitness

evaluation. A lot of systems used to evolve new works of art or music use human

interaction as the fitness function. However this significantly slows down the

evaluation of potential art works. It would be much better if we could let the

computer evaluate the artistic qualities of a candidate solution but this will require a

system that is capable of measuring aesthetic properties. Another challenge posed is

an artistic version of the Turing test: is it possible to create a system that can create

art (or music) that would be recognized by humans for its artistic contribution?

The other chapters focus on applications of evolutionary art and music. Most are

aimed at creating works of art which either look or sound nice or mimic human

artists. However, evolutionary art can also be used for less artistic reasons. An

example of this is the EvoFit program described in chapter 9 to evolve facial

composites of criminals based on the descriptions of eyewitnesses. Nowadays, the

police will probably use sketch artists or composite systems to create pictures but

the latter have a drawback. We perceive faces as a whole, rather than as a collection

of parts, and therefore such composite approaches (where a face is built up of

individual features) are flawed. The EvoFit program shows eyewitnesses sets of 18

generated faces from which they can indicate which two faces look the most like the

suspect. These two faces are then used to evolve the next 18 faces. EvoFit seems to

find more identifiable composites than those produced by existing computer systems

in use in the UK. Frowd and Hancock are also looking at other applications for their

face evolving system. e.g. a version of EvoFit for entertainment purposes which

predicts the appearance of children based on photos of their parents.

Looking at the book as a whole I think the editors have achieved their objectives

and have created a good handbook for evolutionary art and music. It contains

extensive background information and discusses a wide range of techniques and a

large number of application areas. It is intended for a wide readership, ranging from

researchers to artists, but it requires at least basic knowledge of the concepts of

evolutionary computation. Therefore, it is probably more interesting to researchers

already in EC (either beginners or experts) than to computer scientists or artists in

general. For people already active in evolutionary art and music, or who want to

start working in it, I would certainly recommend this book. It certainly deserves a

place in university libraries. Given the number of pages, colour images and the

DVD that accompanies it, The Art of Artificial Evolution is reasonably priced.

96 Genet Program Evolvable Mach (2009) 10:95–96

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