Emergence in Artificial Life
– a philosophically coined view –
Alexander Heußner
Institute of Computer Science
University of Leipzig
Abstract. Emergence is one of the hot-topics of todays science, but this term is neither fixed
by a definition nor actually understood. A possible path to this concept might be via the branch
of Artificial Life, which intends to understand how and why “things” emerge or are introduced
into this world. Ere going to deep into todays rough draft of emergence, a side glance to the
philosophical history of this term is done, based on [Stephan].
This article is mainly based on the ideas of [Cariani] and focuses on the concept of modeling as
the realm of scientific research and the phenomenon of emergence.
1. Introduction
When making toward a relatively unexplored subject like emergence, one needs to choose
a path. On the one hand near to the results already reached and therewith the scientific
tradition, on the other hand one must have the courage to leave this trail and therefore be
able to query the results and the traditional methods.
This article heads towards the term of emergence via a short introduction to the underlying
phenomena and examples to the discussion of emergence in the philosophy of the 19th/20th
century. Then we jump ahead into today’s discussion. Therewith we get to Artificial Life
(ALife) and its way of analyzing and utilizing emergence.
In science you get very fast across the phenomenon of emergence. For computer scientists it is
easily reached via cellular automata and Conway’s famous Game of Life. The most classical
entrance might be the ant and anthill example, which is en detail introduced by Douglas
Hofstadter in his famous “Gödel Escher Bach”→1 .
The questionable fact is: how are the limited capabilities of the particular ant connected
to the whole of the anthill to whom we correspond as an intelligent entity itself. Another
example might be the human body consisting of cellular minor building blocks and an omnium
gatherum of other small lifeforms opposed to the body as a whole with genuine new functions
(metabolism, reproduction. . . ). In this context, some scientists even tend to try a definition
of life itself via emergence:
“life [is a] emergent behavior of complex chemical networks” [Kauffman]
In every situation stated above the underlying question is:
– How to get complex behavior out of simple building blocks?
But we can easily detail this questioning to higher level phenomena:
– Where to derive ‘meaning’ from in neurophysiological systems?
1
“→” is a reference to the glossary in appendix C
– What about creativity? or innovation?
Another vast entrance to the idea of emergence is via dissipative systems→ and phenomena
like the famous Bérnard convection→ . These experiments lead us to further questions like:
– What is the origin of order in the world?
Why does this enormous increase in hierarchical complexity exist?
– How is novelty introduced into the world?
– What is the connection between emergence and synergetics, self-organization, autopoiesis?
All these examples lead us to the assumption that there is an underlying principle to all these
phenomena, something which we will denote by emergence (from the verb ‘to emerge’). At
this point further, more profound questions arise:
– What is emergence?
– Under what conditions do systems exhibit emergent properties?
– How is emergence related to reduction, supervenience, explanation, prediction, and determinism?
The most common approach to such questioning might lead along the history of the concept
of emergence itself. Let us follow the main question about emergence itself and try to find a
definition.
“Emergence means: The whole is more than the sum of its parts”
This definition is the most preferred common sense answer to the upper question, normally
followed by simple examples like the already mentioned ant-anthill or the tone-melodyexample→ . But this answer is unsatisfying, because it opens other questions like: What
is the ‘whole’ ? What is the sum of something? Which are the parts to sum up in this context?
Maybe a look into the strict science of philosophy leads us to further results (see next section).
Without going too deep into this field, two of the classical definitions are worth mentioning:
“emergence serves to mark novelty which mind possesses, while mind still remains equal to
certain neural constellation” [Alexander] (due to [Stephan])
“to the fact that in course of evolution new things/events occur with unexpected and
unpredictable propositions” [Popper/Eccles] (due to [Stephan])
At a first glance, these definitions seem to be in a totally different class of questioning, later
on we are going to see by which philosophical questions they were coined.
The next definition should lead us like a common-use-definition along the next sections:
“[emergence is about the] origin of qualitatively new structures and functions which were
not reducible to those already in existence” [Cariani]
This definition is a kind of counterposition to the simple sum-whole-definition above, avoiding
the bottom-up mereological→ problems with a kind of top-down view (nevertheless, structures/functions are equally difficult terms but maybe more “intuitive”).
“A philosophically coined view” – this subtitle seems strange to a paper written under the
subject of Artificial Life and therefore computer science, but the examined phenomenon of
emergence is really far beyond these specialized sciences. When asking the upper questions
(and also when taking a look at the proposed definitions) one steps forward to very fundamental questions of basic relevance to the whole field of the human’s understanding of himself,
life and the world. In appendix A a starting point for understanding the connections between
Artificial Life and philosophy is given.
2. Overview to Emergence
2.1. Philosophical foundation
The philosophical discipline of emergence was introduced in the end of the nineteenth century
as a countermovement to reductionism→ and vitalism→ . Both tried to solve the questions of
metaphysics→ and cosmology→ . Metaphysics asks questions about the kernel of anything in
existence and cosmology wants to describe the whole of nature in its diversity.
Classical reductionism→ states:
– all changes are ONLY regroupings of simple building blocks
– these regroupings do not introduce novelty
– everything is reducible to simple blocks
In contrast vitalism→ assumes non-reducible building-blocks. For example the phenomenon
of life cannot be reduced only to physical parts, accessorily there exists something like “élan
vital” as a metaphysical ‘glue’.
The idea of emergence is something like a link between these two contrary directions. One
abstains from metaphysical instances and the strong reductionism, therefore emergent phenomena can be grounded onto basic building blocks – but only a posteriori. This means:
novelty arises out of simple building blocks, but we cannot predict it a priori.
For a more detailed review of the origins of emergence in contrast to other philosophical
branches, I will refer the interested reader to [Stephan].
2.2. Renaissance
Today emergence is not more than a minor term in philosophy, but out of several other sciences
the idea is reintroduced into the modern discourse – we could almost call it a “renaissance of
emergence” ([Stephan]).
Mainly three approaches can be distinguished:
– Philosophy of Mind:
This discipline asks about the ontological status of mental properties & states, somewhere
between philosophy and the neuro-sciences.
Emergence is opposed to concepts like logical behaviorism, functionalism, preformationism. . . and gets in contact with the idea of qualia and causality.
– Connectionism is the research and application of neuronal networks, a kind of practical
counterpart to the Philosophy of Mind, in which the idea of emergence plays an intrinsic
basic role.
– Self-organization, chaos→ . . . are the new hot-topics of science. Here we come very quickly
to examples which remind us of emergence (anthill. . . ).
2.3. Cariani’s Classification
In [Cariani] the following classification of emergent phenomena is proposed:
computational emergence – thermodynamic emergence – emergence relative to a model
Without going to deep into detail, this three main categories shall be introduced.
computational emergence this type is derivable via the cellular automaton example; the
basis for everything that happens is computation, a strict formal (syntactic!) mapping
between discrete world-models; order (in this case the emergent phenomenon) is based on
a calculable algorithm describing the determinism of the simple building blocks (in the
above example: the cells); but how to describe the indeterministic behavior of the whole
system (the automaton)? the preferred way is via the mathematical theory of chaos→ on
the computational micro-level - the interaction between the cells
thermodynamic emergence this is the physicists way to emergent phenomena like the upper
mentioned Bérnard convection→ , catalytic networks . . . ; the main difference to the computational approach above is the discreteness or better the indiscreetness of the world; the
kind of mapping applied could be called “semantic”, because the changes are not syntactic
transformations but strongly connected to states of the ‘real world’ (see appendix B); the
emergence of discrete macro-structures out of continuous micro-fluctuations (like Bérnard
cells) is grounded on “noise” as a counterpart to mathematical chaos
emergence relative to a model after a syntactic and a semantic approach, we expect a pragmatic one, and when looking at the basic idea of modeling (appendix B), we would start
our search at the level of choosing the relevant modeling parameters; therefore the basic
mapping is restricted to a symbol-matter-hylomorphism→ ; this is illustrated in the basic
action which is not based on computing or thermodynamic noise – order is derived out
of the complexity of reality itself via the process of linking the symbols of our model to
this ‘real world’; the emergent phenomena is best described by “form-from-formless” or
“definition-from-ambiguity” – new languages and models arise, the process of linking symbols to the world extends the domain of what is expressible and therefore the possibilities
of modeling itself;
The first two categories are evident, especially when looking at the examples given. But why
do we need the third strange kind of category? And what are the relations between these
three types? A more detailed side glance to the most fundamental principle of science –
modeling – might give an appropriate answer.
2.4. Connection to ALife
Before going that deep, an ALife-example of emergence relative to a model should be given.
In ALife computer-simulations are the widest used experimental devices. These simulations
combine the semantic connection of the model to the world (maybe between real ants and the
ant represented by a cell of an automata) and syntactic transformations via the underlying
algorithm. The question “How to interpret ALife-simulations as a whole?” gets out of these
two categories and leads to a pragmatic view onto the whole situation.
Besides phenomena of computational or thermodynamic emergence which are the subject of
the ALife-research , we might be able to perceive emergence in the interconnection of the
model and the semantic foundation of the model (normally the ’world’ modeled after). New
insights emerge for the scientist because of new concepts, theories . . . which are deduced from
the formerly ambiguous situations, which we first called ’emergent’.
The emergent phenomena do not reside only in the simulation but in our ability to model
itself. New concepts emerge like the “being alife of the celluar ant”. . .
This is the basic step towards the basic pragmatic questions: How are ALife-simulations
connected to the world? What kind of interpretation of the model is preferable? Which are
the differences between the simulated world and the actual world?
A Thermodynamic Example
After the above example for a way from computational emergence to emergence relative to
a model, an equivalent way from thermodynamic phenomena should be given. Let’s start
again with the Bérnard convection→ . The most important result is not a phenomenon we
would call emergent, it is the emerging of new terms, new concepts like “bifurcation”, “phase
transition”. . . which widened the scientific horizon by introducing new theories and ideas.
Therefore emergence relative to a model seems to be a very important aspect to the basic
concept of emergence and might be closer to the origin of this concept (see definition of
[Alexander] in section 1.).
3. Emergence and Modeling
The main task of scientific research is modeling. A more basic approach to this topic is given
in appendix B or in the corresponding chapters of [Holland] and [Cariani].
Above we defined emergence as something relative to a model, but what is the kernel of this
statement? What will be its impact onto our understanding of emergence? Why did we get
caught only by the computational and thermodynamic concepts?
3.1. Emergence relative to observer’s frame
A closer look at at the scientific working mode of observation – alike a domain of modeling –
might clear up our understanding of emergence.
After the scientist fixed the observational frame of the corresponding domain, he is able to
precisely talk about emergence (how to attain this “observational view” - see appendix B).
First the analyzed system is observed for a period of time. The observer has now the ability to
build up a model by including all of the syntactic and semantic state transitions he previously
observed or believes to have observed – the primitive state is fixed.
Henceforward the thrilling part commences. The domain is furthermore observed and maybe
new state-transitions are discovered. If no new state-transitions arise, we can call the system
“non-emergent” otherwise we talk of “syntactically emergent” or ”semantically emergent”
either if new computational or if measurement/control-transitions come into existence.
This gets us a post-construction test, if any phenomenon is emergent, emergent relative to
our bottom-up definition of emergence (see section 1), we can classify it after the phenomenon
occured.
Now computational and thermodynamical emergence seem to be a sub-classification of emergence relative to a model.
We lost emergence as a basic idea and got to a relative form of emergence, emergence relative
to a model or more precise relative to a certain observer’s model. This leads up the garden
path, for the very reason that “relative” here means really relative. A simple change in the
basic assumptions can make every simulation appear non-emergent and this is well known
under ALife scientists (for example [Neuhaus]).
The main problem is the initial representation. The main part of ALife research is model
building, the simulation itself is only a minor part. But what makes us confident, that the
emergence we tend to see in phenomena arising out off our simulations are not self-introduced
into the inital model? Not the abolition of emergence is the goal, it is its shifting from assumed
phenomena of a “real world” to relativeness to a model and the emerging of new concepts in
our way of thinking.
Why do we then still need a principle of emergence, when it seems redundant?
Was emergence only a kind of metaphysical principle to avoid the problems with our strong
belief in the objective legality of nature, especially our absolute acceptance of causality as the
basic context of ontology?
3.2. A new meaning of emergence (?)
At this saddle point, we can simply withdraw the concept of emergence, because of its relativeness, but there may be some reasons to make use of it.
Where to go after revealing that emergence is not the basic principle? It is important to find
a new way to deal with the idea of emergence, to let a new meaning of the term emerge.
A constructivistic view
Just start with a Batesonian→ view onto emergence as a principle of explanation.
Without going to deep into the question, if this is only an elusion, not an answer to the
question, I will state, that behind this, we see a kind of meta-way to deal with these underlying
principles. Why not try it with emergence?
If emergence is only an principle of explanation, we get rid of all the problems carved out
above. Emergence seems to be a construct of mankind for dealing with sensual phenomena.
With the school of radical constructivism→ we escape from these problems, but to what price?
This approach seems simple but its simplicity requests a very profound change of our weltbild
– away from assuming a real world to expecting an only “constructed” world, whatever this
stands for. But this very strange approach reminds of the basic task of modeling. We
can exclusively make statements about a model of the world (avoiding the discussion, if
there exists a world which is perceivable for us) – it is legal to talk about computational
or thermodynamical emergence relative to our construct of the world – the world which we
observe. Emergence is used as a principle to explain certain phenomena which are (not yet)
covered by other principles. The new type of emergence relative to a model shifts to a kind
of meta-level of phenomena. It helps to describe the emerging of meta-constructs, constructs
which describe phenomena in other constructs or in other words: models.
Not everyone is ready to leave behind the idea of an existing real world which corresponds
to our internal thoughts and therefore also leave behind the path of common sense. But the
importance of modeling is not negateable, we use models for describing, for handling and for
talking of the complexity of the world.
A pragmatic approach
“the interesting emergent events that involve ALife simulations reside not in the simulations
themselves, but in the ways that they change the way we think and interact with the world ”
[Cariani]
This rises the principle of emergence out of our simulations and the problems with relativeness. Additively we avoid the problem with constructivism, subjectivism and metaphysics.
Emergence is therewith an internal modus operandi of thinking. Not the experimental phenomena emerge, new facts in our understanding of the experiment’s underlying principles
emerge and change our possibilities to “measure and control”, to act. We can cancel computational and thermodynamic emergence or retain them but the effect of the observation of
these phenomena to our thinking ability is still notable.
Hence it is legal, to use the term emergence to describe the Bérnard convection→ , the anthill,
the tone-melody-example→ , the Game of Life,. . . but this all this seems to be an excuse because emergence could be superseded by a new principle of explanation, be eliminated by
another initial representation or be exceeded by a new kind of talking about a situation. This
and only this are the real things that emerge: the theories, the concepts, the new ideas.
To conclude, emergence is one of the basic principles of life itself, but because of our dealing
with models in science we are only able to observe emergence in our models and therefore
emergence relative to our models. If there are emergent phenomena outside of our models
our outside of our mode of thinking? – This is not verifiable for us, it is a case of scientific
belief and belongs to the creed of our individual “Church of Science”.
4. Synopsis
What is the implication of the attempt to deconstruct the usage of the word emergence? In
my eyes, today a lot of the basic principles would need a scrutiny: causality, quality, physical
laws and their relation to the reality. . .
But not to overthrow them. Maybe the way would lead back to the sources, the sources of
science as a whole, the human questioning about the sensual perception of our environment.
Why do we (or did we) need a concept like emergence?
Emergence is “the” fundamental phenomenon when dealing with life, especially with ALife.
Because of the scientific method of model-building, we are not able to make statements about
emergence in real life, but we can simply investigate life in simple models. The only limit is
the computer as a finite state and deterministic device, which is a strong constraint to ALife’s
research project.
The emerged new way of viewing emergence is an emergent phenomena itself. The new
perspective onto the basic act of modeling leads to the importance of the ‘old’ emergent
phenomena to our inventory of concepts and theories. These emergent phenomena helped
us to introduce new ideas into our everydays scientific life. But beside it, there are other
ways of how novelty is introduced into our constructed world, like a radical change of our
observational frame. A vast field lies open in front of us to be explored (and exploited).
There is no reason to waive the term ’emergence’ in our everyday’s life, because we use it
natively in our telling stories, our “natural way we autonomous agents talk about our raw
getting on with it” [Kauffman]. Talking is based on language as a “model” of reality, and
the concept of something emerging is one of our basic ones. In this context, emergence as
a meta-concept, a mode of thinking, gets close to intuition and creativity. This might be a
vaster framework to take a look at emergence.
References
[Bedau] Mark Bedau: “Philosophical Aspects of Artificial Life”
in Varela et al. (ed.): “Towards a Practice of Autonomous Systems: Proceedings of the First European
Conference on Artificial Life”, pages 494–503, 1992.
[Cariani] Peter Cariani: “Emergence and Artificial Life”
in Christopher Langton (ed.): “Artificial Life II” Addison-Wesley 1992
[Holland] John Holland: “Emergence”, Oxford Univ. Press 1998
[Kauffman] Stuart Kauffman: “Investigations”, Oxford Univ. Press 2000
[Krohn] Krohn/Küpers (ed.):
“Emergenz: die Entstehung von Ordnung, Organisation und Bedeutung”, Suhrkamp 1992
[Neuhaus] Wolfgang Neuhaus: “Leben im Computer?”,
http://www.heise.de/tp/deutsch/special/robo/15676/1.html, Telepolis, Heise 2003
[Prigogine] Grégoire Nicolis, Ilya Prigogine: “Die Erforschung des Komplexen”, Piper Munich 1987
[Stephan] Achim Stephan: “Emergenz”, Dresden Univ. Press 1999
A. Artificial Life and Philosophy
“The field of ALife is betting on the success of a central working hypothesis: that the essential
nature of the fundamental principles of life can be captured in relatively simple models ”
[Bedau]
What is the difference then to the oldest ’modeling-science’ – philosophy? It is the kind of
questions asked, and the strong leaning to questions on the meta-level.
Some fundamental Questions: (excerpt of [Bedau]’s 14 questions)
– What is life? (list of characteristics, special chemical patterns, the principle of evolvabiltiy
or self-reproduction . . . )
– What is the nature of life’s characteristic processes, such as selforganization, self-reproduction,
metabolization, adaption, purposiveness and evolution?
– What is the relation between life and mind?
– Under what conditions, if any, is a simulation of a life process an artificial but real instance
of life? (Which features are necessary in the model?)
– Is life a functional notion?
– What ethical implications does ALife research have for humanity and other extant forms
of life?
– What ethical responsibilities would we bear to artificial forms of life that we created?
(computer viruses. . . )
This is only a rough overview, but even the philosophical unbiased reader will see the similarity
of these questions to the ones which have been asked for nearly 4000 years (and far beyond
that point). ALife will not give the answer to all these questions, in which philosophers often
seem to be stuck, but might give a different approach to the possible ways of answering them.
The other way round, the ALife-scientist normally gets stuck in a niche, maybe specialized
computer simulations without connection to the ’real world’ (whatever this might be), and is
– in my eyes – not willing to see the enormous field of answers already given to the questions
which arise in his scientific experiments. In my eyes, both sciences could inseminate each
other and leave behind the strong separation built up through history. In ancient times there
was only the one questioning after the human being, life and the world. Mankind tried to
solve these questions with all possible concepts and ideas no matter if one was a philosopher
or a scientist. I think ALife today has the chance to integrate the old ideas with modern
concepts and the wonderful experimental device of computers. Maybe this is the beginning
of a new kind of scientific approach. . .
B. Modeling
Modeling is one of the most important tools of mankind. From clay-modeling to models of the
atmosphere for weather forecast it is always the same basic idea: because of the complexity
of even the smallest parts of the universe (domains), one needs to build up a model, which
tends to be simpler than the thing described and therefore is minimizing the tremendous
complexity.
In the language of mathematics and computer science: because of the vastness of the trajectory space and the nearly uncountable number of variables, a restricted, manageable and
computable model is needed.
The computer makes a new type of models possible: adaptive systems, which learn to adapt
to things and can evolve itself (self-modifying programs). The goal in modeling is a commutative interpretation of the world:
world(t)
“laws”
/ world(t’)
interpret.
model(t)
algorithm
/ model(t’)
This is the simplest model of modeling itself. A state of the world at a time t is interpreted
by a model at time t. The changes of the world – which could be described by “laws” in
a wide sense, maybe these laws will never be extractable for us – have their counterpart in
algorithmic rules of changing the model to the next time t0 . This operation could be seen
as a formal term transformation, a strict syntactic operation. Whereas the operation of interpretation reminds of a semantic transformation – it is only about denotation. To finalize
this linguistic approach, the pragmatics can be seen as the choice of the interpretation and
algorithms in use, the connection of the modeling functions to the world in a feedback kind
of fashion.
Now the goal is easy to be seen, the interpretation of the world at t0 should be equivalent to
the computed model at this time.
As with every simple idea, the problem is hidden in the most important detail: How to build
a model? How to choose the right operations? What do we need as building blocks?
The basic structure lies in the choice of the underlying basic approach. The next table will
give a very naı̈ve overview, but might help the reader to connect the basic steps to already
familiar concepts of today’s knowledge representation.
basic action:
model world
interaction of elements
configuration of elements
constraints of interactions
agent-view:
domain
agents
change in time
simple rules
transition-functional:
states
transition function
strategy (game theoretic)
To complicate the whole thing, an observer is introduced, he/she/it chooses the model of the
world, perceives the reality and builds up the information to a model etc.
world
choose
/ model of world
The choice of the model determines, how the reality is connected to the model in a kind of
measuring operation and how the model can be used to plan or describe things in the reality
out of the model – a kind of controlling action, because the observer is able to act on this
information.
measure
world l
-
“image” of world
control
To sum up, computation is the syntactic operation of modeling, measurement the semantic
one, and the choice of the appropriate model the pragmatic. To involve the whole picture:
the observer is always included in some larger model of the domain and therefore never able
to view the situation in an objective way (what is never possible – throughout a larger ‘meta’model exists).
To conclude, modeling is one of the most basic tools of science and of our everyday life, but
it is a far cry from being subsumable to the human, who is modeling out of himself in a kind
of naı̈ve and native way.
C. Glossary
Bateson wrote some wonderful essays in a kind of dialogue-form he named ‘metalogue’;
I would like to introduce one of the most famous:
a daughter asks her father: “what is an instinct?” and he answers: “An instinct, my
dear, is a principle of explanation.” and therefore she asks about what it explains; the
father answers: “Everything, almost everything, what you want it to explain.” — “Does
it explain gravity?” — and the father gives an example, how to explain the phenomenon
of gravity as an instict of the moon. . . but the daugther does not capitulate: “But what
then is explained by gravity?” — “Nothing, because gravity is a principle of explanation.”
and now the father introduces a definition of the term principle of explanation: it is a
statement which connects two descriptive statements.
[translated from a citation of this metaloge in [vonFoerster: “Wahrheit ist die Erfindung
eines Lügners”, Carl-Auer ’98] p46]
Bérnard convection this is a classical example of a dissipative system→ ; the basic experiment
is like this: there are two thin metallic plates in a small distance (like physicists like it:
these plates have an infinte surface and no thickness), between them is a fluid (like water or
oil); now we heat up the lower plate and look into the fluid; after some time, at a ‘special’
temperature, we see an effect like in our own atmosphere: the fluid near to the lower plate
heats up, rises to the upper plate, cools down and sinks again down; a kind of circular
motion exhibits and the strange phenomenon is the building of a large amount of such
small circles all along the plates, each neighbour with a reverse spin; when the temerature
is furthermore increased, the cells dissolve into a kind of thermodynamic chaos; this effect
seems to be very abrupt and the split of the homogenous fluid into cells (with a different
spin) are a typical example of loss of symmetry (for a more detailed view see [Prigogine])
Chaos in this sense is far away from big huddle or the biblic tohuwabohu; this chaos is acausal
but it is (for mathematicians) deterministic, even if it is uncomputable; this theory allows
a better handling of all the phenomena of chaos, order (its counterpart) and the small
“edge of chaos”, in which lies the main focus of ALife
Cosmology in this context is NOT the minor subcategory in physics but a kind of counterpart
to metaphysics; cosmology’s question are more of the physical kind: about the material
structure of a world as a whole in space and time
Dissipative Systems due to [Prigogine]: dissipative systems are systems with irreversible
processes – these are not invariant to a change of the direction of time; classical physics is
based on conservative systems, in which all processes can easily be turned around in time
Gödel-Escher-Bach “Gödel, Escher, Bach - an Eternal Golden Braid” by Douglas Hofstadter;
“This book reads like an intellectual Grand Tour of hacker preoccupations. Music, mathematical logic, programming, speculations on the nature of intelligence, biology, and Zen are
woven into a brilliant tapestry themed on the concept of encoded self-reference. [. . . ]” [the
Jargon Dictionary: http://info.astrian.net/jargon/Bibliography/Godel Escher Bach.html];
beneath all the examples, the ant-anthill metaphor and the relation between tone and
melody are introduced en detail even for the non-mathmatician
Hylomorphism hyle means material, morphe – form, these two principles are combined and
every existing entity has this two parts as ’becoming by courtesy of something’ and ’becoming something’, in philosophy a third principle is added: steresis, the possibility for
the entity to be or not to be.
here the morphe and form are represented by matter (what exists in the ‘world’) and
symbol (its representation in the model)
Mereology the greek µρoς means ‘part’ and mereology is the science of the part-wholerelationship; especially in contrast to set theory
Metaphysics is the philosophical discipline “behind the physics” (this is what metaphyisics
means), which is concerned with questions about the existence of everything (and also
things, pyhsicists do not try to explain, like: god, belief, love. . . )
Radical Constructivism is a very controversial branch of philosophy; starting point is a theory
of cognition based on systemtheoretic, cybernetic and neurophysiologic results; in a too
short version: every form of cognition is only a construct of an observer; the “real world”
is not reality – reality is something which is forever percepted, observed, invented, and
only constructed; this is not to be confused with solipsism, who states only the existence
of a ‘me’ and denies a reality as only a fiction of this ‘me’
Reductionism these theses state that every entity of some domain are reducible to other
entities of another domain (building blocks); the reductionism here is a strict materialistic
one, like the famous atomism: everything is built up of small undividable material building
blocks – atoms
Tone-melody-emergence the basic building blocks of music are tones, the higher system
level is a melody, composited of tones; but not all properties of the melody (like tempo,
expressiveness. . . ) can be reduced to the tones or a “sum of tones”
Vitalism these concepts are a countermovement to mechanism; the world is not only describable by mechanics; there exists a vigor, comparable to the importance of a soul to “glue”
up all the material (and mechanic) body parts in some philosophical concepts