Darwin Grosse

It isn’t very often that I’m excited to buy a US$150 book. But when I first saw the release of "The Oxford Handbook of Algorithmic Music" (which we can abbreviate as 

), I knew I was in. Edited by Alex McLean (of TidalCycles and AlgoMech fame) and Roger T. Dean (who also edited "The Oxford Handbook of Computer Music"), the book enjoys both editorial experience and deep content knowledge. The question is: how can you write a book about algorithmic music when the artists, their music and the technologies are so closely entwined? McLean and Dean chose a great approach: allow the artists to speak for themselves.

OHAM-Cover.png

In the first piece in the book, McLean and Dean are quite clear about this perspective. They point out that the theoreticians and practitioners of algorithmic music are, in most cases, the same people; from George Lewis through Mark Fell and beyond, the individuals exploring the ideas of algorithmic music are also creating the language and producing the music that are their most compelling examples. By allowing this blurring of the theory/practice line, each of the entries in this book contain both theoretical concepts and practices-based stories.

Many of the ‘stories’ behind algorithmic music development are highly personal stories, and the book embraces that aspect of the art. The editors chose to group the information into four high-level 

, with each part having a sub-section dedicated to practice, articles focused on performers/artists that have a focused and concrete perspective – based on their experience in performing or developing the rules that they cite as the heart of their work.

The first part is labeled “Grounding Algorithmic Music”, and it places the practice of algorithmic music within the broader scope of music creation and study. This section features some fascinating discussions, from the editors introductory review piece to discussions of an algorithm’s interaction with standard musical concepts. The Practice section features some well-known names, including Laurie Spiegel (who provides some very concise ideas about the reason to use algorithms) and George E. Lewis, who weaves the history of his composition process with the ideas that drive it.

In the second part, entitled “What Can Algorithms in Music Do?”, we find a number of pieces that offer insights into the impact of algorithms – and especially the available tools – on the world of the composer/performer. There are a number of articles that introduce specific tools and techniques; Thor Magnusson and Alex McLean introduce a deep discussion of patterns using the 

 programming languages, while other authors provide insights on the use of constraints, machine learning algorithms and biological influences on algorithmic development. Charles Roberts and Graham Wakefield provided an especially interesting article entitled “Tensions and Techniques in Live Coding Performance” which exposes some of the difficulties – and opportunities – presented by realtime code/algorithm performance.

Part three (“Purposes of Algorithms for the Music Maker”) moves things in a practical direction – focusing on the benefits algorithms can provide to artists, and how to improve access to algorithms for artists. For example, Margaret Schedel’s overview of visual-to-audio transcoding is a beautiful compendium of the different ways of using images for sound design. It puts a unique spin on the concept of algorithms in music making, helping place algorithms in an idea-space that isn’t purely mathematical.

Likewise, in Carla Scaletti’s article “Sonification ¹ Music”, we get a breakdown of sonification as a practice, and how deeper thinking about data mapping and the presentation of data is necessary. It also describes both the differences and similarities between sonification and music composition, and – like many of the articles in this book – is willing to warn of some of the pitfalls that might prove troublesome in ones practice.

The fourth and final part is called “Algorithmic Culture”, and this is where things get really interesting. There are pieces suggesting algorithm use in music education, pop culture and audience reception and participation. These outward-facing views of the practice are revealing because they point to the authors imagining the effect of algorithmic music on broader culture. But there are also several articles that are inward-facing, discussing the technologies, societies and politics that make the community what it is – and that also help one to see how it can further grow.

This part wraps up with a closing article by McLean and Dean that acts as a bookend to the initial piece. In this short article, the two editors describe their own work and how their work has matured over time. It’s a great way to tie all of the preceding information together and help you see that algorithmic music options are more than just theories – they are artistic decisions just as relevant as ones’ selection of a musical instrument.

OpenBook-OHAM.png

A number of years ago, a friend introduced me to a technique for reading ‘serious’ material: sit at a table with the book and a computer. When you run into new ideas or hear about a particular performance (or artist), fire up a browser and learn more 

. "The Oxford Handbook of Algorithmic Music" gave me plenty of opportunities to do this, since so many of the writers included information about compositions or performances that I could find on YouTube or Spotify. As the authors were dropping names and listing citations, a number of new trails revealed themselves, revealing additional background material to open my mind.

I also didn’t read the book front-to-back. I did consume most of the first part, since it set the stage for understanding algorithmic music as an artform. But from there I skimmed articles, landing on ones that caught my attention for deeper reading. Some of these – like the afore-mentioned Schedel and Roberts/Wakefield pieces – ended up generating pages of notes and ideas, all of which I was anxious to take into my studio for further exploration. I can imagine coming back to the book, picking up different chapters, and experiencing similar feelings. This feels like a book that will keep on giving, and I think it is a refreshing way to take on new ideas.

It isn’t very often that I’m excited to buy a US$150 book. But when I first saw the release of "The Oxford Handbook of Algorithmic Music" (which we can abbreviate as OHAM), I knew I was in. Edited by Alex McLean (of TidalCycles and AlgoMech fame) and Roger T. Dean (who also edited "The Oxford Handbook of Computer Music"), the book enjoys both editorial experience and deep content knowledge. The question is: how can you write a book about algorithmic music when the artists, their music and the technologies are so closely entwined? McLean and Dean chose a great approach: allow the artists to speak for themselves.


Many of the ‘stories’ behind algorithmic music development are highly personal stories, and the book embraces that aspect of the art. The editors chose to group the information into four high-level parts, with each part having a sub-section dedicated to practice, articles focused on performers/artists that have a focused and concrete perspective – based on their experience in performing or developing the rules that they cite as the heart of their work.

In the second part, entitled “What Can Algorithms in Music Do?”, we find a number of pieces that offer insights into the impact of algorithms – and especially the available tools – on the world of the composer/performer. There are a number of articles that introduce specific tools and techniques; Thor Magnusson and Alex McLean introduce a deep discussion of patterns using the ixi and Tidal programming languages, while other authors provide insights on the use of constraints, machine learning algorithms and biological influences on algorithmic development. Charles Roberts and Graham Wakefield provided an especially interesting article entitled “Tensions and Techniques in Live Coding Performance” which exposes some of the difficulties – and opportunities – presented by realtime code/algorithm performance.

A number of years ago, a friend introduced me to a technique for reading ‘serious’ material: sit at a table with the book and a computer. When you run into new ideas or hear about a particular performance (or artist), fire up a browser and learn more within the context of the reading. "The Oxford Handbook of Algorithmic Music" gave me plenty of opportunities to do this, since so many of the writers included information about compositions or performances that I could find on YouTube or Spotify. As the authors were dropping names and listing citations, a number of new trails revealed themselves, revealing additional background material to open my mind.

Highly recommended!

The Oxford Handbook of Algorithmic Music
Oxford Handbooks
1st Edition, February 15, 2018
Edited by Alex McLean and Roger T. Dean
ISBN: 9780190226992

Creating a book that can effectively cover a topic as wide-ranging as algorithmic music has many challenges. Let's see how editors Alex McLean and Roger T. Dean weave both the technical and the practical in The Oxford handbook of Algorithmic Music!

book-review-the-oxford-handbook-of-algorithmic-music

By the way - there are a bunch of used copies out there floating around for quite reasonable prices. Be sure to check out your usual favorites for these things (The Strand, Powell's Alibris.com). Sorry I already scored that 

 inexpensive copy in mint condition a while back, but....

By the way - there are a bunch of used copies out there floating around for quite reasonable prices. Be sure to check out your usual favorites for these things (The Strand, Powell's Alibris.com). Sorry I already scored that really inexpensive copy in mint condition a while back, but....

Very cool, love your articles, as usual. :-)

All the Composers, Sound Designers and even Improvising Musicians do Algorithmic Music ... The Computer is the Persons head and the Algorithms are all the decision methodology that he uses to put events in his musical design or output. They don't call it Algorithmic Music , I don't know why. In what this book can be useful?

All the Composers, Sound Designers and even Improvising Musicians do Algorithmic Music  ... The Computer is the Persons head and the Algorithms are all the decision methodology that he uses to put events in his musical design or output. They don't call it Algorithmic Music , I don't know why.  In what this book can be useful?

You are right - pattern creation and 'rules' are a big part of what people use for music development. This book examines what those rules are for different kinds of people, or what tools they use to enable those rules. Or even, sometimes, how they believe the rules were developed in the first place.

Thanks for the shout out Darwin! I felt honoured to be part of the book honestly, it's a wonderful collection and I keep dipping back into it and following the traces it leads to, just as you say.

Thanks for the review, Darwin! The publishers tell me that a paperback version will be out soon. You can also find preprints for many of the chapters here -> 

https://zenodo.org/communities/algomusic/?page=1&size=20

Thanks for the review, Darwin! The publishers tell me that a paperback version will be out soon. You can also find preprints for many of the chapters here -> https://zenodo.org/communities/algomusic/?page=1&size=20 
Take care, all


Book Review: The Oxford Handbook of Algorithmic Music