=Paper=
{{Paper
|id=Vol-2068/milc6
|storemode=property
|title=Overviewing a Field of Self-Organising Music Interfaces: Autonomous, Distributed, Environmentally Aware, Feedback Systems
|pdfUrl=https://ceur-ws.org/Vol-2068/milc6.pdf
|volume=Vol-2068
|authors=Phivos-Angelos Kollias
|dblpUrl=https://dblp.org/rec/conf/iui/Kollias18
}}
==Overviewing a Field of Self-Organising Music Interfaces: Autonomous, Distributed, Environmentally Aware, Feedback Systems==
<pdf width="1500px">https://ceur-ws.org/Vol-2068/milc6.pdf</pdf>
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Overviewing a Field of Self-Organising Music Interfaces:
Autonomous, Distributed, Environmentally Aware,
Feedback Systems
Phivos-Angelos Kollias
CICM – Centre de recherche en Informatique et Création Musicale
Esthétique, Musicologie, Danse et Création Musicale
Université de Paris VIII
Paris, France
soklamon@yahoo.gr
ABSTRACT theory, complexity) and which is formed spontaneously by
This paper aims to identify and discuss the music field of individual cases of composers-researchers with unique yet
self-organising music: an emerging field based on different converging approaches. A music field where common
forms of self-organising music interfaces, that is to say concepts such as self-organisation, emergence, environment
‘intelligent’ sound/music systems characterised among and feedback are applied in different levels, technically or
others by autonomy, distributed/decentralised feedback metaphorically. We are aiming in connecting the dots among
processes and of environmental awareness. A music field individual cases which are fed conceptually and technically
based on systems-oriented concepts (cybernetics, general by the same systems-oriented context, and which result to
systems theory, complexity) and which is formed very similar technological means.
spontaneously by individual cases of composers-researchers
with unique yet converging approaches. We are describing By investigating different cases based on similar approaches
the general context of self-organising music and presenting of intelligent music interfaces, our aim is to outline the
different cases of composers-researchers that deal with the existence of a common ground; a common ground mainly
subject both from a technical and a theoretical perspective. shaped by common technological characteristics which
We conclude the paper suggesting the search for a system- consequently may have aesthetic consequences and
oriented shared musical language in order to broaden and implications.
evolve the field’s musical though. Our investigation concerns cases that contribute to the
KEYWORDS emerging field of self-organising music with some form of
self-organising music; systems-oriented music; feedback originality – through an active model or some suggested
instruments; audio feedback systems; generative audio advancement. Furthermore, we are interested in approaches
systems; autonomous music agents; artificial music where the technological domain is tightly interconnected
intelligence; autonomous instruments; feature-feedback with the compositional material and the conceptual/aesthetic
systems; adaptive synthesis; audible eco-systemic interface; principles in use. Our investigation is not interested in cases
eco-composition; performance ecosystems. that are producing music through self-organising algorithms
acquired by other researchers; where the algorithms are used
INTRODUCTION as ‘found objects’ without the knowledge of their conceptual
We can observe and identify a new and active field emerging origins.1 We are focusing on outlining some representative
from individual cases (or small teams) of composers- cases in order to establish a common ground of self-
researchers interested in what we can call self-organising organising music. The collection of the approaches we
music: a music field based on different forms of self- expose, even if it is far from exhaustive, intends to be
organising music interfaces, that is to say ‘intelligent’ representative.
sound/music systems characterised among other features by
autonomy, distributed/decentralised feedback processes and But, can we really talk about a consistent music field of ‘self-
of environmental awareness. A music field based on organising music’? In other words, do the similarities and
systems-oriented concepts (cybernetics, general systems convergences among composers allow us to speak of a
musical movement? This being the case, what are the
© 2018. Copyright for the individual papers remains with the authors.
Copying permitted for private and academic purposes. common characteristics among composers-researchers that
MILC '18, March 11, Tokyo, Japan. form a music movement of this kind? Then again, can we
1
We have to clarify that, we are not considering music created by artistic value expressed by algorithms/instruments designed by
algorithms/instruments designed by others than the composer others or without detailed knowledge on the principles of the
himself/herself less important; nor do we believe that music by algorithms’/instruments’ design – for instance, new works for
composers without explicit knowledge of the used orchestra performed by traditional instruments.
algorithms/instruments creates less significant music. On the
contrary, we can imagine several works of great originality and
talk about an aesthetic movement or are they just conceptual specific and it is a clearly linked term to the systemic
and technical coincidences that cannot legitimise a general epistemology.
classification into a movement? Or is it maybe our natural
We are interested in the self-organising work from a
tendency to look for patterns everywhere, driving us to
compositional perspective. However, if a work is primarily
project meaning into something amorphous and arbitrary –
created in order to be listened to,3 the listener’s perspective
as if we were looking for recognizable patterns in the night
is of equal importance: the self-organising work as a process
sky by making links between stars? And if we can talk about
of the listeners cognition; in other terms, the perceptual
a self-organising music, what are these similarities and
manifestation of the work as a self-organising process
convergences between the different composers? What are the
between the listener's active listening and sound [14].
means of expression and the language of this musical
stream? What are its aesthetic characteristics and what are Here, we aim to outline the field around the concept of a self-
the limits? organising music, by seeking technological as well as
SELF-ORGANISING MUSIC INTERFACES
conceptual similarities and convergences among approaches
We can describe self-organising music interfaces, in general of certain composers-researchers that we believe to be
terms, as those interfaces composed by generative music representative. We present some surveys dealing with the
processes directly influenced by their sonic environment; subject in similar ways yet under different denominators.
where the sonic behaviour emerges as a ‘complex adaptive We have previously suggested an elementary schematic
system’ [8], resulting from numerous interaction at a basic model of self-organising music [12], [14] (Figure 1). Based
organisational level. on second-order cybernetics [7], the model describes a
Dynamically controlled audio feedback is an elementary yet system as a feedback loop with two inputs: the goal-input
crucial form of self-organisations as it is found at the basic and the perturbations-input. Considering the system as an
organisational level: sound organises sound itself, i.e. sound organised whole, the model describes the entire system as an
self-organises. For that, controlled audio feedback is the emergent function of a feedback loop; an emerging system
most common feature of self-organising approaches. by individual interacting feedback functions. The model
describes the whole system’s emerging function; but also, it
This is why denominations based on the concept of feedback can describe any organisational level at which self-
are relevant enough to describe our field and give to the organising processes take place, regardless of their temporal
concept of feedback the central importance it deserves. For scale.
that, the use of the term feedback is common: audio feedback
systems [11, 17], feature-feedback systems [8] or feedback
instruments [15]. We are dealing with music interfaces
including at least one feedback function as a vital structural
part. It’s important to clarify that the feedback function
should be playing a vital role for the entire use of the system,
and without which, the whole system would not be
functional.2
The feedback function is not only important for the audio
domain, but also, it is used as a control signal, giving the
possibility to observe and to guide other processes that are
mapped with. Consequently, in this approach the
composer/sound artist, instead of working only in the audio
domain with DSP, he/she is also working in ‘composing the
interactions’ with ‘control signal processing’ (CSP) [5].
Although we recognise the central importance of feedback’s
role, we have a preference for the term ‘self-organising’. That
is because, the term ‘feedback’ has been broadly overused, Figure 1. A schematic model of a self-organising music
to the extent that it does not suggests any particular interfaces [12]
epistemology anymore. Instead, ‘self-organising’ is more Each system’s goal can be determined and be altered
(statically or dynamically) by an external user. Alternatively,
2 3
A counterexample would be a feedback function observing the Considering the case of music composed purely for the pleasure
sonic environment in order to preserve energy by switching off the of the composing process per se. Even in this case, music is
whole system – something important in terms of energy efficiency, transmitted and it is perceived through sound medium. Therefore,
but which does not actively influence the sonic result. even if the music will never be heard by an auditor, its creator will
be its unique auditor.
in more advanced systems, the goal can be self-determined seems to be a schematic explanation of the different
and self-regulated by the system. In the case of a self- categories rather than a definition; that is why it may include
determined goal, we are talking about a second-order system features that do not affect the essence of self-organising
– in other terms, a learning system [6] – capable of changing music understanding (such as internal or external triggering),
the way in which it reacts with the environment. but it may be important for understanding the general
classifications.
We have previously described the self-organising work
manifesting as an emergent complex; resulting from the
interactions between some given structures and a certain
performance/installation context; interactions which are
defined by a model [12]. In self-organising music, the
element of autonomy offers certain vitality to the work, an
expressive spontaneity and a direct communication among
the real-time sound production of the work, the acoustic
space and the participant-listeners. The work’s autonomy
may cause the composer to relinquish a great degree of direct
control over the end result. Nevertheless, we have suggested
that it is possible to create a type of intelligent music
interface where a desirable series of behavioural states can
be provoked each time; a series of states which will be
similar even when the circumstances change [12]. In this Figure 2. A general scheme of feedback systems according to
approach, a user/performer listens and changes behavioural Sanfilippo and Valle [17].
states accordingly; in the meanwhile, the self-organising
music system responds by continuously adapting to the new Morris uses the term feedback instruments [15]. Although his
conditions. The sounds result is a direct sonification of each model is the result of his personal observations, we find it
state’s adaptation. This way, there is an intentional control of relevant in describing the essential characteristics of
the overall sonic properties’ self-organisation. The feedback instruments. Morris’ classification includes four
user/performer is in direct interaction with the self- categories [15]:
organising music interface while the user-interface is sound 1) the loop can be:
per se. a) electric
As a case study, we have previously discussed our work b) electroacoustic
Ephemeron (2008-2018) [12] [13] [14]; a self-organising c) digital
work with a constantly developing algorithm4, emerging 2) the intervention, the modifications on the feedback
each time through systemic interactions among 8-21 sound, for example may be:
speakers, 2-4 microphones and the specific sonic a) delay period change, which creates a pitch-shift
environment of the performance/installation. effect
b) phase shift, which changes certain resonant modes,
Sanfilippo and Valle’ investigation uses the term feedback as in the case of a violin touching a string results
systems [17], comparing and presenting eighteen different in a natural harmonic.
approaches – including our Ephemeron interface – with the c) filtering change, which alters the active frequency
use of feedback as common denominator. Their investigation range of a feedback or causes a range of resonant
attempts to expose an analytical framework comprised of six frequencies.
categories: 3) the interruption, the action of stopping the feedback:
1) information encoding: analogue or digital a) manual interruption, for example switching off a
2) information rate: audio signal or control signal microphone
3) environmental openness: open or closed b) a shutter, like an envelope that dynamically forms
4) trigger mode: internal or external the feedback’s amplitude
5) adaptability: absent or present c) a pitch shifter, changing the self-amplification of a
6) human-machine interaction: absent or present frequency range
4) the excitation, which triggers the feedback resonance:
Similarly to our schematic model described above (Figure 1), a) unintentional sounds – ‘noise’
Sanfilippo and Valle present a schematic diagram in order to b) intentional sounds – ‘played’ sounds
visualize their typology (Figure 2). Their diagram’s goal
4
Before each presentation, the algorithm is updated with technical
improvements in terms of stability and performance, but also with
additional functionalities which expand its capabilities.
c) iterative feedback sounds – the use of another particle-birds. The complexity of bird cloud behaviour
feedback as a sound source for the feedback emerges through the local interactions between individual
system birds [16]. Similarly, Blackwell & Young apply the same
principle in the micro-temporal domain by using the
Surges, Smyth and Puckette talk about generative audio paradigm of granular synthesis: sonic grains take the role of
systems, i.e. feedback network systems focused on dynamic self-organising particles which form self-organising swarms
filtering [18]. In this type of system, the output signal is used of sound, what they call the swarm granulator [3]. In this
to dynamically control the coefficients of all-pass filters that practice, we find a bottom-up approach in which time scales
are redefined to be flexible yet stable. They refer to them as emerge – from the micro-structural level to the meso-
‘audio systems’ in order to distinguish them from ‘music structural level – from which consequently larger formal
systems’: as they explain, in audio systems, there is a strong structures emerge.
coupling between lower-level organisation sound production
and higher-level sound organisation [18]. Holopainen also uses the terms autonomous (like Collins)
and self-organisation (like Kollias or Blackwell & Young)
Kim, Wakefield and Nam also talk about audio feedback to synthesise the term self-organised sound with autonomous
systems [11]. It is interesting to note their interaction with instruments [9]. He also uses the terms feature-feedback
our music research and in particular the concept of systems or adaptive synthesis. Although referring to the same
intentional control of sound properties we have previous field his interest in the subject is non-real-time, unlike the
described [12]. Similarly to what we suggest, Kim et al. approaches we have discussed above. Consequently, self-
suggest a goal-oriented feedback system in which, the organisation takes place as a set of non-linear algorithmic
intended sound characteristics are specified as goal- interactions, without a physical environment (acoustic or
conditions [11]. However, in their approach, they replace the social); they are abstract interactions that occur in a virtual
level of self-organisation in the system performed by a space and time. For that, we may consider ‘autonomous
human-agent by adding an additional organisational level instruments’ (at least according to Holopainen's use) rather
including machine learning techniques; a process that as adaptive effects, including simulated perceptual
observes and guides the parameters to the desirable goal- characteristics, using feature extraction techniques. As he
state each time. says, it is a special case of algorithmic composition, which
Collins talks about autonomous agents, where their design resides at the sub-symbolic level [9]. Way may consider his
responds to questions of musical artificial intelligence [4]. approach as a case of non-environmentally aware self-
His discussion concerns systems with features of machine organising music – since there is no physical environment.
learning techniques emulating perceptual abilities. The Di Scipio's approach has an important leading role in the
machine learning techniques use a simulation of human field of self-organising music as one of the first to contribute
perception pertaining to the peripheral and central auditory theoretically and musically. Di Scipio proposes his audible
system. However, the algorithms perceptual abilities can eco-systemic interface, in which music emerges as an
change or exceed the original human abilities from which ecosystem of interactions between the algorithm, the sound
they were modelled. We stretch Collins’ remark, that the environment and the resulting sound [5]. He talks about an
artificial intelligences of these systems do not have a audible interface, because all interactions take place at an
physical presence, as is the case with any manifestation of auditory level, avoiding any visual representation. Although
artificial intelligence techniques [4]. We add that, he refers to the term ecosystem, his references are closer to
autonomous agents, similarly to any self-organising music system theories (interactions between systems and parts of
systems, have no embodied intelligence. They are only a systems) than those of ecology (interactions between
piece of software coded in a piece of hardware [19]. organisms in an environment).
Blackwell & Young use the term self-organised music5 [3]. Keller seeks to find a common field between different
Their approach is based on swarm intelligence [2], a case of composers for what he calls eco-composition: as the common
distributed self-organisation: the system’s global behaviours denominator, he defines the integration of natural
emerge as a complex whole comprised of local agents with phenomena in the compositional process, integrated with the
simple behaviours. Blackwell & Young's approach is based formal, perceptual and/or social factors in the work’s
on the original work of Reynolds, who created visual material [10]. As he says, many composers use
simulations of bird swarms [16]. In Reynold’s approach, environmental concepts, but with different terminologies
each unit has a rather simple movement behaviour: Each bird depending on the focus of their interests – just as is the case
has its own autonomous behaviour, while at the same time, of the perspective we suggest through self-organising music.
each bird is a particle of the swarm, interacting with all other It is interesting that in Keller’ suggestion, all factors – the
5
We note here that our use of the term of self-organisation into where the work is self-organising. Whereas, the case of Blackwell
music is a direct reference to systems theories (see Kollias 2008 & & Young is a rather special case of music self-organisation.
2011), independently from Blackwell & Young. For our part, we
use the term self-organising music to describe all cases of music
formal, the perceptual, the social – are interconnected, explain different things; or conversely, others may use
having an equal importance, without any of them being different terms to deal with similar themes. Consequently,
considered as an extra-musical factor. In addition, we should the music discussion tends to be in rather vague terms,
mention his suggestion of the correlation between different dealing with extra-musical subjects such as metaphors,
time scales and emerging perceptual scales that pass from the modelling through visual representation, or imprecise
personal perspective to the social perspective (Figure 3). abstractions.
Even if we find several system-oriented concepts in his
However, apart from the more or less vague common
perspective, Keller tries to establish a field based on
concepts, a field of convergence between different authors
ecological studies.
arises from the fact that they publish and discuss their
algorithms’ blueprints (or their circuits) or even the
algorithms’ code. Consequently, this results in a more
concrete source of discussion and an important tool for
technical exchange. Compared with systems terminology
which is a meta-language, and thus highly abstract by
definition, an algorithmic blueprint is a clear and well-
defined reference point: i.e. diagrams with well-defined
symbols and connections representing interconnected DSP
modules.
Nevertheless, it cannot change the fact that it is a point of
convergence around purely technical characteristics. Thus, it
does not suggest a specific set of aesthetics. We would like
to emphasise that, until now, to the best of our knowledge,
we cannot find a musical language based on systems
epistemology which is really linked with musical material;
Figure 3. Time scales according to the ecological paradigm either a systems’ musical language that deals equally with
[10]. the organisation, creation and processing of sound per se,
Waters refers to performance ecosystems [20]. He describes and not merely with poetic references or connections with
music as a complex system from the viewpoint of sonic and techniques in a vague manner.
social perspective. He distinguishes three parts: the We would like to ask some open questions: would it be
performer and his ‘corporeality (bodilyness)’, the instrument possible to reach a point where we will have and use a
and the goal-oriented approach and finally the environment system-oriented shared musical language? A language with
and its ‘otherness’ in regard to the system of performer- which we could describe, discuss and imagine what we call
instrument. In his survey, he refers to various approaches that self-organising music – as is the case of the conventional
include ecosystem relationships through technology. musical language for notated music, or for instance the
According to Waters, the performance ecosystem is not spectromorphological terminology, for acousmatic music?
merely a metaphor inspired by natural ecosystems. On the This could be a powerful tool of broadening musical thought
contrary, he suggests that the musical trend is interconnected through systemic conceptual and methodological tools.
with our corporality, our sensory agility and our interaction Where music would really be genuinely linked with systems
with the environment [21]. thinking and not just inspired by its concepts.
CONCLUSION However, even if it was possible, who would take the
We have investigated and identified a new and active field of responsibility to ‘impose’ a language with the possibility to
composers-researchers who deal with the subject of what we be used by many? Would it be someone able to take the
can call self-organising music. A music whose means of decisions for everyone, by preparing a language and
expression is the computer; the tools are microphones, exposing it in the form of an ‘aesthetic manifesto’ – as was
controllers, sensors and so on; the expression material is the the case rather often in past art history? Nonetheless, if a
"live" electroacoustic sound that includes the source of its ‘specialist’ proved to be able to do this, from our systemic
production but also the space in which it is expressed. viewpoint, this would appear to us as an authoritarian
We can identify a shared tendency inspired by system- tendency while imposing itself on the possibility of social
oriented theories towards a self-organising music practice. self-organisation. Or otherwise, what if it was a team of peers
However, we can find as many different approaches as – that is to say, respectable colleagues on the field with equal
composers who practice them. Each composer tends to and similar skills – with its own criteria in determining a
choose a perspective according to his/her own priorities and systemic language? As this was the case with Macy
values to interpret the systems concepts in a different conferences, the very source of systems thinking, organised
manner. In this sense, several authors use the same terms to in order to construct a shared consensual metalanguage [1]
[22]. Once again, from our viewpoint, we can see the danger
of a certain kind of elitism, and again the problem of a 10. Damián Keller, and Ariadna Capasso. 2006. New
dictating and opposing the tendency of a social self- concepts and techniques in eco-composition.
organisation. Organised Sound 11, 1: 55-62.
Since the demand for a common language that can be shared 11. Seunghun Kim, Graham Wakefield, and Juhan Nam.
and used by the community cannot be imposed, the only 2016. Augmenting environmental interaction in audio
legitimate way would be again a collaborative project. And feedback systems. Applied Sciences 6, 5: 125.
if we are talking about true self-organisation, this project 12. Phivos-Angelos Kollias. 2008. Ephemeron: Control
itself should be equally self-organising. A kind of project that over Self-Organized Music. In Proceedings of the 5th
would determine the conditions under which a common International Conference of Sound and Music
language could be built or chosen, tested and shared. We Computing (SMC '08), 138-146. Revised version of
could imagine a form of wiki capable of responding to this 2009 published in: Hz Music Journal, 14. Retrieved
demand, where any choice would be genuinely open, and the December 12, 2017 from
language self-organising. We leave the proposal open. http://www.fylkingen.se/hz/n14/kollias.html
ACKNOWLEDGMENTS 13. Phivos-Angelos Kollias. 2011. The Self-Organising
We would like to thank Triantafyllos Gkikopoulos for his Work of Music. Organised Sound, 16, 2: 192-199
thorough remarks and for his precious reflections. In
14. Phivos-Angelos Kollias. 2017. Vers une pensée
addition, we acknowledge the important feedback from the
musicale orientée-système : l’œuvre musicale auto-
anonymous peer-reviewers of this article. Finally, we would
organisante. PhD dissertation. University of Paris VIII,
like to thank Vincent Van Heerden for proof reading the
Paris, France.
article.
15. Jeffrey Morris. 2007. Feedback instruments:
REFERENCES Generating musical sounds, gestures, and textures in
1. Ludwig von Bertalanffy. 1968. General System real time with complex feedback systems. In
Theory: Foundation, Development, Applications. Proceedings of International Computer Music
Reference to the revised edition, 1969. George Conference (ICMC '07), 469-476.
Braziller, New York.
16. Craig W. Reynolds. 1987. Flocks, herds and schools: A
2. Eric Bonabeau, Marco Dorigo, and Guy Theraulaz. distributed behavioral model. ACM SIGGRAPH
1999. Swarm Intelligence: From Natural to Artificial computer graphics 21, 4: 25-34
Systems. Oxford University Press, New York,
NY/Oxford, UK. 17. Dario Sanfilippo and Andrea Valle. 2013. Feedback
systems: An analytical framework. Computer Music
3. Tim Blackwell, and Michael Young. 2004. Self- Journal 37, 2: 12–27.
organised music. Organised Sound 9, 2: 123-136.
18. Greg Surges, Tamara Smyth, and Miller Puckette.
4. Nicholas M. Collins, 2006. Towards autonomous 2016. Generative audio systems using power-
agents for live computer music: Realtime machine preserving all-pass filters. Computer Music Journal 40,
listening and interactive music systems. PhD 1: 54–69.
Dissertation. University of Cambridge, Cambridge,
UK. 19. Francisco J. Varela. 1988. Cognitive Science. A
cartography of Current Ideas. Reference to the
5. Agostino Di Scipio. 2003. ‘Sound is the interface’: enlarged French version: Invitation aux sciences
From interactive to ecosystemic signal processing. cognitive. 1996. Editions du Seuil, Paris.
Organised sound: An international journal of music
technology 8, 3: 269-277. 20. Simon Waters. 2007. Performance ecosystems:
Ecological approaches to musical interaction. In
6. Hugh Dubberly, Paul Pangaro, and Usman Haque. Proceedings of Electroacoustic Music Studies Network
2009. ON MODELING: What is interaction? Are there (EMS '07)
different types?. Interactions 16, 1: 69-75.
21. Simon Waters. 2011. Performance ecosystems:
7. Francis Heylighen, and Cliff Joslyn. 2001. Cybernetics Editorial. Organised Sound 16, 2: 95-96
and Second-Order Cybernetics. Encyclopedia of
Physical Science & Technology. Academic Press, New 22. Norbert Wiener. 1948. Cybernetics, or control and
York, 155-170. communication in the animal and the machine.
Reference to the 2nd paperback edition, 1965. The MIT
8. John H. Holland. 2006. Studying Complex Adaptive Press, Cambridge, MA.
Systems. Journal of Systems Science and Complexity
19, 1: 1-8.
9. Risto Holopainen. 2012. Self-organised sound with
autonomous instruments: Aesthetics and experiments.
PhD Dissertation. University of Oslo, Oslo, Norway.
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