Neuroergonomics and sociogenesis, Lectures part 1

i d i iNeuroergonomics and sociogenesis
Internationa Society of Biourbanism
Summer School 2014
bi b i i f @bi b iwww.biourbanism.org ‐ info@biourbanism.org

Biourbanism Manifesto
Antonio Caperna, Alessia Cerqua, Alessandro Giuliani, Nikos A. Salingaros, Stefano SerafiniAntonio Caperna, Alessia Cerqua, Alessandro Giuliani, Nikos A. Salingaros, Stefano Serafini
Biourbanism focuses on the urban organism, considering it as a hypercomplex system, according to its internal and external dynamicsg g yp p y g y
and their mutual interactions.
The urban body is composed of several interconnected layers of dynamic structure, all influencing each other in a non‐linear manner.
This interaction results in emergent properties, which are not predictable except through a dynamical analysis of the connected
whole This approach therefore links Biourbanism to the Life Sciences and to Integrated Systems Sciences like Statistical Mechanicswhole. This approach therefore links Biourbanism to the Life Sciences, and to Integrated Systems Sciences like Statistical Mechanics,
Thermodynamics, Operations Research, and Ecology in an essential manner. The similarity of approaches lies not only in the common
methodology, but also in the content of the results (hence the prefix “Bio”), because the city represents the living environment of the
human species. Biourbanism recognizes “optimal forms” defined at different scales (from the purely physiological up to the ecological
levels) which, through morphogenetic processes, guarantee an optimum of systemic efficiency and for the quality of life of the
i h bit t A d i th t d t f ll th l d ti t l h til i t hi h d t fit i t i di id l’inhabitants. A design that does not follow these laws produces anti‐natural, hostile environments, which do not fit into an individual’s
evolution, and thus fail to enhance life in any way.
Biourbanism acts in the real world by applying a participative and helping methodology. It verifies results inter‐subjectively (as people
express their physical and emotional wellbeing through feedback) as well as objectively (via experimental measures of physiological,
social, and economic reactions).
The aim of Biourbanism is to make a scientific contribution towards: (i) the development and implementation of the premises of
Deep Ecology (Bateson) on social‐environmental grounds; (ii) the identification and actualization of environmental enhancement
according to the natural needs of human beings and the ecosystem in which they live; (iii) managing the transition of the fossil fuelaccording to the natural needs of human beings and the ecosystem in which they live; (iii) managing the transition of the fossil fuel
economy towards a new organizational model of civilization; and (iv) deepening the organic interaction between cultural and physical
factors in urban reality (as, for example, the geometry of social action, fluxes and networks study, etc.).

References
• Nikos Salingaros Twelve Lectures on Architecture Algorithmic Sustainable Design Solingen: Umbau Verlag 2010• Nikos Salingaros, Twelve Lectures on Architecture. Algorithmic Sustainable Design, Solingen: Umbau Verlag, 2010.
• Nikos Salingaros, Antonio Caperna, Michael Mehaffy, Geeta Mehta, Federico Mena‐¬Quintero, Agatino Rizzo, Stefano Serafini,
Emanuele Strano, «A Definition of P2P (Peer‐To‐Peer) Urbanism», AboutUsWiki, the P2P Foundation, DorfWiki, Peer to Peer
Urbanism (September 2010). Presented by Nikos Salingaros at the International Commons Conference, Heinrich Böll Foundation,
Berlin, 1st November 2010.
• Milena De Matteis, Stefano Serafini (eds.), Progettare la città a misura d’uomo. L’alternativa ecologica del Gruppo Salìngaros: una
città più bella e più giusta, Rome: SIBU, 2010.
• Joseph P. Zbilut, Alessandro Giuliani, Simplicity. The Latent Order of Complexity, New York: Nova Science Publishers, 2007.
• Christopher Alexander, The Nature of Order, 4 vol., Berkeley, CA: Center for Environmental Structure, 2002‐2005.
• Grant Hildebrand Origins of architectural pleasure Berkeley CA: University of California Press 1999• Grant Hildebrand, Origins of architectural pleasure, Berkeley, CA: University of California Press, 1999.
• Stephen R. Kellert, Edward O. Wilson (eds.), The Biophilia Hypotesis, Washington: Island Press, 1993.
• René Thom, Esquisse d’une Sémiophysique, Paris: InterEditions, 1991.
• Antonio Lima‐de‐Faria, Evolution without Selection. Form and Function by Autoevolution, London – New York – Amsterdam:
Elsevier Science, 1988.
• Gregory Bateson, Mind and Nature: A Necessary Unity (Advances in Systems Theory, Complexity, and the Human Sciences), g y y y y y p y
Cresskill, NJ: Hampton Press, 1979.
• Conrad H. Waddington, Tools for Thought, London: Jonathan Cape Ltd., 1977.
• Edgar Morin La Méthode: La Nature de la Nature Paris: Seuil 1977Edgar Morin, La Méthode: La Nature de la Nature, Paris: Seuil, 1977.
• Ludwig von Bertalanffy, General System Theory, New York: George Braziller, 1968.

iNeuroergonomics
urban designurban design
sociogenesisg
by Stefano Serafini
“Wh t if i t d f b ki th th d i f iti ld t ll“What if, instead of breaking them, the design of cities could naturally
feed social ties? There must be a way for urban planners to make
cities more human‐centred and livable, by focusing on how the built
environment affects sociality.”
International Society of Biourbanism - Summer School 2014

ABSTRACT
The International Society of Biourbanism (ISB) is organizing a Summer school in neuroergonomics and sociogenesis, to be held in
Artena, Italy, on July 13th‐20th 2014. The program offers seven full days of lectures, practical workshops, and design studios, with
international experts for exploring how to design urban environments able to revive, support, nourish, and enhance sociality and
human relationships. Seven additional days will be devoted to study the ancient urban codes of two biophilic Italian towns, Artena
and Segni – a research headed by the distinguished Professor Besim Hakim. The results of this study will be brought to theand Segni a research headed by the distinguished Professor Besim Hakim. The results of this study will be brought to the
international Workshop on socio‐spatial transformation under the state of emergency in Greece, on August 1‐9.
Any full social interaction includes a fundamental part of the human person: the body. Therefore, it always occurs in a place. Space
becomes place when intentionality is at stake, and landscape, nature, buildings, and forms in space have a meaningful interaction
with life An urban place the social environment par excellence has therefore always a biopolitical meaning Designing the urbanwith life. An urban place – the social environment par excellence – has therefore always a biopolitical meaning. Designing the urban
environment means designing the biopolitical preconditions of human life, including the chances for freedom, social interaction,
political practice, health, and well‐being.
The placelessness of modern and contemporary cities is not an aesthetic issue – it’s social, and it severely affects citizens’ self‐
determination and quality of life, including the ability to connect to each other and to a nourishing environment. Thus, the ISB school
aims at a needful social and cultural change of cities by design.
Biourbanism is rethinking urban design by joining contributions from the domains of epistemology, neurophysiology, environmental
psychology, economics, biopolitics, urban studies, service design, and sociology. The results outline the possibility of a paradigm shiftp y gy, , p , , g , gy p y p g
in urban practice. This carries a peer‐to‐peer approach which involves designers, inhabitants, and places.

A biopolitical issue
The third ISB summer school will complete a cycle.
Having dealt with neuroergonomics as a prerequisite
to urban planning (Neuroergonomics and Urban
Design, 2012), followed by its small‐scale applications
for propagating systemic effects over the entirefor propagating systemic effects over the entire
urban organism through biourban acupuncture
(Neuroergonomics and urban placemaking, 2013),
participants in the 2014 International Summer School
in Biourbanism will focus on how to design spaces
that facilitate and reinforce social relations with athat facilitate and reinforce social relations, with a
special program in neuroergonomics and
sociogenesis.
This issue is of paramount importance because
although modern cities gather millions of people in,
they tend to overlook and break down human
relations, as Marx and Engels already noticed almost
a century and a half ago.[1] This decade, cities have
become the living environment for half of theg
planet’s population for the first time in history, and
according to urban migration and growth trends, 64%
and 86% of the developing and developed world
respectively will be urbanized by 2050 (67% overall,
i e 2 7 billion more people than today) [2] whilei.e. 2.7 billion more people than today),[2] while
urban exploitation of land will double in less than 20
years.[3]
What kind of design is behind such an
environmentally unsustainable, speedy, and
d h b h
Fig. 1 Three phases of urban land use in Shenzen, China: 1988, 1996, 2010
(source: Google)
dehumanizing urbanization phenomenon?

If you look carefully, modern cities have been meant as machines – economic growth catalysers. Several scholars accuse Le Corbusier
of being the evil genius of such an urban conception;[4] yet one should date its origins back to the very dawn of the Industrial age,
with roots even into the phenomenon of the first ghetto (Venice, 1516).[5] In fact, modern cities are designed to functionalize the
horizon of human life according to production. And that’s precisely why they break social connections. In a way, the early subsidiary
and social role of cities has been morphed into the capitalistic subsumption[6] device par excellence. This happened by firstly
transforming the physical space of cities through ghettoization, zoning or gigantism. Design has never been innocent.[7]
The industrial revolution has accelerated the transformation of streets, squares, and common environments into paths for goods, and
turned dwellings into individualistic boxes, piled into suburbia. This has allowed less and less room for delightfulness and social
connections, hence most of the “ugliness” of modern towns addressed by several urban critics like Tönnies, Simmel, Weber, Wirth,
Marcuse, Bauman, Augé, Alexander and Salingaros.
Post‐industrialism led to a leap in the quality of city morphing: as finance has long dematerialized capitalism, the postmodern city is
heading towards a dematerialization of places.
As we know, space has become almost irrelevant for producing surplus value thanks to the deployment of information technology
and its global dominance. Smart cities of today – the citadels of global capitalism – don’t need to destroy places anymore, because
finance acts in the hyperspace of infosphere, and hyperspace is potentially and instantly everywhere. [8]
On one hand, this has worsened the hostility of urban environments toward humans. The history of progressive interfacing and loss
of human connection to reality (i.e. nature, other human beings, and themselves) has been outlined by Ivan Illich.[9] Telephoney ( , g , ) y [ ] p
devices, Internet, and social media seem to widen the range of sociability, while on the contrary they’re actively regimenting it. The
medium is the message as notoriously McLuhan put it; and the message shapes and steers the messenger towards the purpose for
which the medium was built. So to speak, what we write down on Twitter is Twitter itself. A self‐referential production and
consumption of a stream of information may be amusing, but it in fact happens in physical solitude and distracts awareness and life
from real human actions and interactions setting aside the needful and nourishing intentionality of bodyfrom real human actions and interactions, setting aside the needful and nourishing intentionality of body.
All that is fleshy, wild, dirty and unexpected has no room in the clean design of the contemporary ICT city, not surprisingly. What we
really see going through a coded and engineered human settlement is, instead, a forest of abstract signs referring to its hyperreal
backbone – a kind of pure essence of capitalistic ties who conquered, and substituted both social connections and space from within.
h h l h h h k f d l k h b [ ]
The hypercity lives within the remaining shuck of modern towns, like a hermit crab.[10]

This is the ultimate result of a gradual transformation of human places into plugs for subsuming the wholeness of human life (and of
nature, through human consumerism), according to the evolution of our society. Paraphrasing Bertrand Russell, one could say that
place serves not only to give room to political freedom but to make possible political freedom which could not exist without it.[11]
The transformation of contemporary urban environments into “non‐places” is thus a means to monopolize all aspects of human life
within a physical and cultural horizon that deflects social intentionality into passive cattle‐like individualism. “Non‐freedom” is not a
blatant dictatorship, as placelessness is not a horrific instantiation of chaos. It rather occupies subtly the imaginary for eliciting and
controlling desires, it builds paths which take only to planned destinations. As an expression of the society of spectacle,controlling desires, it builds paths which take only to planned destinations. As an expression of the society of spectacle,
contemporary urbanism needs a certain aesthetics and, so to speak, an etiquette. The most evolved cities exhibit it abundantly in
their neat, efficiently fancy urban organization and architecture.
Given that real human connection doesn’t consist of
h tti b t d d f h ichatting about ready‐made news nor of having
drinks together, everyone notices how it is
objectively difficult to cultivate authentic sociability
in the rushing routine that our lives turned out to
be. A real interest towards the other, solidarity, even
conflict, and in the end truth, are being banished by
our urban society, as they have become irrelevant
for our Hobbesian vision of the world.
Nevertheless on the other hand dematerializationNevertheless, on the other hand, dematerialization
is setting free many urban places, especially where
the system controls fail, i.e. where raw physics and
biology matter. Human reactions flourish like weeds
between the cracks, in the scarce interstices where
th ’ littl f f lthere’s little or no room for performance, goals,
possession – and thus subsumption plugs can’t
work.[12] Locality is furthermore living a new dawn,
and it’s showing its ability to counter‐exploit the
global interface tools for reviving its local social
connections.[13] Fig. 2 Rotterdam, The Netherlands (source: S. Serafini)

Solutions for a shift in urban planning
That the results of urban planning are not brilliant in this regard is perhaps the main topic for urban researchers and practitioners
debate. May we refer after Biourbanism to the Ruin Academy by Marco Casagrande, the Project for Public Space in the United States,
the Centre for Advanced Spatial Analysis in London, Jan Gehl Architects in Copenhagen, the Association for the Biourban Study of
Monotowns at the Kazakh Economic University, etc.
Every architect and urban designer who hasn’t surrendered to the sterile logic of rules, looks forward to a built environment that
positively affects society. Who doesn’t desire a city more human, authentic and happy, where social relations unfold and grow free?
This is the problem we will address during the summer school.
To do that we have first to deconstruct the mainstream mindset about the society but we don’t aim at doing it ideologicallyTo do that, we have first to deconstruct the mainstream mindset about the society, but we don t aim at doing it ideologically.
Evidence is enough: things have gone so wild that we need something more empirical and direct for dealing with the classical cage of
modern urban thinking, after ideology has already showed its powerlessness.
Thus here you are with biophilia, constructal law, evidence‐based design, laws of form, complexity, neurology and biology – the
subjects that biourbanism connects together for offering a new vision over urban studies. The human attitude towards the alive
world, and the reasons behind such an attraction, that we call neuroergonomics, has a lot to say about design and human wellness,
despite architecture biennales, up‐to‐date journals, and politicians.
Stemming from evidence‐based design, neuroergonomics is a discipline that merges neuroscience and ergonomics in order to matchg g , g p g g
design with human biological and psycho‐neuro‐immunological wellness. It scientifically upholds the call for a human‐centred design
by overhauling the user experience design, because it measures the real psycho‐physical effects regardless of fashion, ideology,
culture, or current use.
Thinking out of the box allows us for example to look at how ancient settlements like Artena happened to be so harmonious andThinking out of the box allows us, for example to look at how ancient settlements like Artena happened to be so harmonious and
well‐working according to context, human feeling, the material and social needs of the time. That has nothing to do with stylistic
nostalgia and aesthetics. The diatribe between “modernism” and “vernacularism”, for example, has no relevance here.

This is why the zooming‐out contribution by the keynote speaker, Professor Besim Hakim, is very relevant to our summer school.
Professor Besim Hakim, Fellow of the American Institute of Certified Planners, a Harvard graduate in Urban Design, is a distinguished
Fig. 3 Artena, Italy (source: Wikipedia)
Professor Besim Hakim, Fellow of the American Institute of Certified Planners, a Harvard graduate in Urban Design, is a distinguished
expert in Mediterranean urban codes. He devoted more than 40 years of research studying why Mediterranean cities from the 6th to
the 19thcenturies AD are so beautiful and well fitting. His work showed the existence of bottom‐up urban codes, based on social
connections and commons, rather than on a formal top‐down blueprint envisioned by an architect. Ancient Mediterranean towns
unfolded outwards according to proscriptive, local, shared rules that were understandable and enforceable by everyone, and that
formed a fundamental tool for people to peer to peer build the place they were inhabiting [14]formed a fundamental tool for people to peer‐to‐peer build the place they were inhabiting.[14]
The social core of this ancient bottom‐up approach to the urban environment is very logical, and has shown to have some interesting
properties from the biourbanism point of view: the urban forms generated through such a process share fractal and biophilic
qualities with the natural environment. They match not only with sociality, but also with neurophysiological homeostasis, a
phenomenon that deserves a scientific explanation.

A humble sensorial experience for action
The term “sociogenesis” is a word derived from Greek which means “the generation of the society”, not “the building of the society”.
Socio‐generative design aims at raising, developing, and facilitating social relations between people according to their own specific
dynamics that already exist, and connect better the individual with the world. It works through architectural, urban, organizational,
economic, and educational interventions that focus on relations, by re‐sewing a broken but still existing net.
Thesocio‐generative design is thus particularly complex and sensitive. It requires multi‐disciplinary contributions on the one hand,
and the active participation of the community on the other. As such, the process is itself socio‐generative, and an integral part of the
subject. The project will have a dynamic character, because sociogenesis never reaches an end. Like a living body, it is constantly
adapting to changes. The product of socio‐generative design is therefore a system, not merely a structure. It includes a procedural
homeostatic flow an adaptive attitude and a constant transformation/processing (both physical and cognitive) of the place and of itshomeostatic flow, an adaptive attitude, and a constant transformation/processing (both physical and cognitive) of the place and of its
affordances, along with a dynamic writing of urban codes.
The ISB summer school will take place in the ancient borgo of Artena. Participants will share the place with the local community, will
sleep in their houses, eat and work in the same vibrant and real set they are going to study, because knowledge is not about reading
or talking, but primarily about experiencing, feeling, observing, and doing. One must be humble when seeking for the reality to open
up.
After the ISB summer school, Professor Hakim will lead a research project on local codes (Artena, Segni) from July 21st to 27th We
expect members of ISB and other scholars to join and participate to this unique opportunity.p j p p q pp y
The ISB Summer School in Artena will be followed also by a complementary workshop in Heraklion, Greece, co‐organized with the
Autonomous Research Lab of Crete. The subject for this workshop is socio‐spatial transformations under the state of emergency.
Scholars will gather in Crete to discuss the interrelations between design, economics and politics, and the results of the summer
school will be provided as material ready to be processed into social action The program consists of three labs (P2P/Open Sourceschool will be provided as material ready to be processed into social action. The program consists of three labs (P2P/Open Source
Logistics, Beyond Economics, and Biophilia/Design and Power), a sensory seminar, a site‐specific design studio and field trips. Most
relevant will be the space given to Peer‐to‐peer Urbanism as a participatory urban planning approach to design, construct, and repair
cities in a way that anyone may choose: participate, share, and modify theories, methods, and implementation technologies at any
time. Peer‐to‐peer Urbanism is “open source urbanism”, by the people, for the people.[15]

The goal is to delineate the systemic implications of local responses to recession and to explore socio‐spatial practices that contradict
and negate the current economic restructuring regime. A new urban design is needed for building authentic cities – polis – able to
bring back politics, i.e. the bottom‐up dialectic search for a new economic system, and the longing for a more authentic, human,
social, and meaningful life.
NOTES
[1] Friedrich Engels, The condition of the working‐class in England in 1844. Panther Edition: London 1969[1] Friedrich Engels, The condition of the working class in England in 1844. Panther Edition: London 1969
http://www.marxists.org/archive/marx/works/1845/condition‐working‐class/index.htm
[2] United Nations, Department of Economic and Social Affairs, Population Division. World Urbanization Prospects, the 2011 Revision:
Highlights. UN: New York 2012 http://esa.un.org/unup/Documentation/highlights.htm
[3] Shlomo Angel, with Jason Parent, Daniel L. Civco, and Alejandro M. Blei. Making Room for a Planet of Cities (Policy Focus Report).
Lincoln Institute of Land Policy: Cambridge Mass 2011 https://www lincolninst edu/pubs/dl/1880 1195 Angel%20PFR%20final pdfLincoln Institute of Land Policy: Cambridge, Mass 2011 https://www.lincolninst.edu/pubs/dl/1880_1195_Angel%20PFR%20final.pdf
[4] Simon Richards, The Antisocial Urbanism of Le Corbusier. Common Knowledge XIII (2007) 1, pp. 50‐66.
[5] Stefano Serafini, Sign, Cognition, Body. Lecture at the Summer school in neuroergonomics and urban placemaking, Artena, Italy,
July 23rd 2013.
[6] Karl Marx. Results of Immediate Process of Production. Appendix in: Capital. Volume 1: A Critique of Political Economy. Penguin
Classics: London 1990 pp. 943–1084.
[7] Nikos Salingaros. Complexity and Urban Coherence. Journal of Urban Design, vol. 5 (2000), pp. 291‐316
http://zeta.math.utsa.edu/~yxk833/UrbanCoherence.html
[8] Antonio Caperna & Stefano Serafini, Biourbanism as a new framework for smart cities studies, in Vinod Kumar (ed.) Geographic
Information Systems for Smart Cities. Copal Publishing: Ghaziabad/London 2013.y p g /
[9] Ivan Illich, La perte des senses. Fayard: Paris 2004.
[10] Jean Baudrillard, L’échange symbolique et la mort. Gallimard: Paris 1976.
[11] “Language serves not only to express thought but to make possible thoughts which could not exist without it”, as quoted by Neil
Postman, Teaching as a conserving activity. Delacorte Press: New York, 1979, chap. 8.
[12] Marco Casagrande Biourban acupuncture From Treasure Hill of Taipei to Artena ISB: Rome 2013[12] Marco Casagrande, Biourban acupuncture. From Treasure Hill of Taipei to Artena. ISB: Rome 2013.
[13] Igor Calzada, Adolfo Chautón, Domenico Di Siena. Macro, Meso, Micro. Systemic Territory Framework from the perspective of
Social Innovation. 2013 http://macromesomicro.com/book/
[14] See for example Besim Hakim, “Mediterranean urban and building codes: origins, content, impact, and lessons”, Urban Design
International, XIII (2008) 1: 21‐40.
[ ] k l h h ff h
[15] Nikos Salingaros with A. Caperna, M. Bauwens, D. Brain, A. M. Duany, M. W. Mehaffy, G. Mehta, F. Mena Quintero, E. P. Petit, A.
Rizzo, S. Serafini, E. Strano. P2P Urbanism. 2010 http://zeta.math.utsa.edu/~yxk833/P2PURBANISM.pdf

INDEX
1. Algorithmic sustainable design: theoretical key concepts – Antonio Caperna
2. A kind introduction to complexity – Alessandro Giuliani
3 Biourbanism and sociogenesis – Stefano Serafini3. Biourbanism and sociogenesis – Stefano Serafini
4. Algorithmic sustainable design: morphogenesis – Antonio Caperna
5. Pattern language – Antonio Caperna
6. Generative processes – Besim S. Hakim6. Generative processes Besim S. Hakim
7. Algorithmic sustainable design: “the Nature of order” – Antonio Caperna
8. Neuroscience and Design – Menno Cramer
9. Biophilic architecture and biophilic design – Antonio Capernap p g p
10. Urban sociology – Katherine Donaghy
11. Biourban city – Antonio Caperna
12. Paracity – Menno Cramer, Katherine Donaghy
13. Placemaking – Angelica Fortuzzi
14. Weak architecture – Diogo Teixeira

Algorithmic Sustainable DesignAlgorithmic Sustainable Design
theoretical key conceptstheoretical key concepts
Antonio Caperna, PhD
antonio.caperna@biourbanism.org
Lecture 01International Society of Biourbanism - Summer School 2014
Lecture 01

Key wordsKey words
biourbanism homology
evolutionary biology architecture
b iurbanism biophilic design
morphogenetic process life sciencesmorphogenetic process life sciences
dynamic complex systemsy p y

An epistemological paradigm
hift ll d " i tifishift was called a "scientific
revolution" by epistemologist
and historian of science Thomas
Kuhn in his book The Structure of
Scientific Revolutions.
A scientific revolution occurs,
according to Kuhn, when
scientists encounter anomalies
that cannot be explained by the
Kuhn used the duck‐rabbit optical illusion to
that cannot be explained by the
universally accepted paradigm
within which scientific progress
has thereto been made Kuhn used the duck rabbit optical illusion to
demonstrate the way in which a paradigm
shift could cause one to see the same
information in an entirely different way.
has thereto been made.
The paradigm, in Kuhn's view, is
not simply the current theory, but
th ti ld i i hi h itthe entire worldview in which it
exists, and all of the implications
which come with it

The science of the last 150 years hasThe science of the last 150 years has
profoundly shaped our culture and our
i ili icivilization
This has changed:
 O K l d Our Knowledge
 how we look at ourselves
 how we think and feel,
 how we view our social and political institutions,
 the findings of science have intentionally separated the process of forming
mechanical models of physics from the process of feeling

The Cartesian method showThe Cartesian method show
aprioristic reduction and
i i i l iaprioristic analysis
(Descartes, 1637, pp. 20‐21).( , , pp )
analysing complex things into simpleanalysing complex things into simple
constituents (its parts)
understood a system in terms of its
isolated partsisolated parts
Phenomena can be reduced to simple cause
& effect relationships governed by linear laws
 l ti hi t i t t
relationships are not important

Descartes’ mind‐matter ontological
dualism. Mind and matter are dua s d a d atte a e
separated substances.
This means that they have an
independent existence and theindependent existence and the
difference between the two is infinite.
(see Descartes 1642; Heidegger 1962;(see Descartes, 1642; Heidegger, 1962;
Fuenmayor, 1985).

Shifting from the old paradigm to theShifting from the old paradigm to the
complexity one
The reform in thinking is a key anthropological and historical problem. This
implies a mental revolution of considerably greater proportions than the
Copernican revolution. Never before in the history of humanity have the p f y f y
responsibilities of thinking weighed so crushingly on us. (E. Morin)

The meaning of a systems approach
What is that which distinguishes a systems approach from other approaches?
The meaning of a systems approach
" t h" t " h""systems approach" means to "approach"
or "see“ things (or phenomena) as s stemsor "see“ things (or phenomena) as systems

Systems ThinkingSystems Thinking
The systems approach relates to considering wholes rather than parts, taking
ll h i i iall the interactions into account.
General Systems Theory (GST)
The interdisciplinary idea that systems of any type and in any specialism can all
be described by a common set of ideas related to the holistic interaction of thebe described by a common set of ideas related to the holistic interaction of the
components. This non linear theory rejects the idea that system descriptions
can be reduced to linear properties of disjoint parts.

complexity
disorganized complexity
life sciences

non‐random interaction between the parts
properties not dictated by individual parts
It t t “ ” ith t " idi h d"
Organized
complexity
Its structure “emerge” without any "guiding hand".
complexity
may be understood in its behavior among the
properties through modeling and simulation
constraints reduce the variations from elementconstraints reduce the variations from element
independence and create distinguishable regimes of
more‐uniform, relationships

Disorganized complexityDisorganized complexity
In Weaver's view, disorganized complexity results from the particular system
h i l b f t ( illi f t )having a very large number of parts (millions of parts, or many more).
Though the interactions of the parts in a "disorganized complexity" situation
can be seen as largely random, the properties of the system as a whole can be
understood by using probability and statistical methods
(example of disorganized complexity is a gas in a container)

Organized complexityOrganized complexity
In Weaver's view, resides in nothing else than:
‐ The non‐random interaction between the parts.
‐ The coordinated system manifests properties not carried or dictated by
individual parts.
‐ The organized aspect of this form of complexity vis a vis to other systems than
the subject system can be said to "emerge," without any "guiding hand".
‐ The number of parts does not have to be very large for a particular system to
have emergent properties.
‐ A system of organized complexity may be understood in its propertiesA system of organized complexity may be understood in its properties
(behavior among the properties) through modeling and simulation, particularly
modeling and simulation with computers.
(example of organized complexity is an ants colony)

Complexity is hard to define!Complexity is hard to define!
I h diff d fi i i i diff fi ldIt has too many different definitions in different fields.
Seth Lloyd’s paper: “Measures of Complexity: a non‐exhaustive list” gives
something like 42 different definitions.
These different definitions are useful for measuring different aspects of g p
systems.

COMPLEXITYCOMPLEXITY
The interaction of many parts giving rise toThe interaction of many parts, giving rise to
difficulties in linear or reductionist analysis
due to the nonlinearity of the inherent
circular causation and feedback effectscircular causation and feedback effects.

A complex systemA complex system
involves a number of
elements, arranged in
( ) hi hstructure(s) which can
exist on many scales.
These go throughThese go through
processes of change
that are not describable
by a single rule nor areby a single rule nor are
reducible to only one
level of explanation,
these levels often
include features whose
emergence cannot be
predicted from their
current specifications.

A scientific approach structured around a new paradigm:
l S tcomplex Systems
Made of many non‐identical elementsade o a y o de t ca e e e ts
connected by diverse interactions
NETWORKNETWORK

Common Principles of Complex SystemsCommon Principles of Complex Systems
 components or agents
 Nonlinear interactions among components
 No central control
 Emergent behaviors

International Society of Biourbanism - Summer School 2014Source. Wikipedia

COMPLEX SYSTEMS EXAMPLESCOMPLEX SYSTEMS EXAMPLES

“The construction and structure of graphs or networks is the key to
d di h l ld d ” ( bá i)
Nodes: chemicals (substrates)
understanding the complex world around us” (Barabási)
Nodes: chemicals (substrates)
Links: bio‐chemical reactions
Metabolic Network Neuronal Network

Social studySocial study
Sarah
Ralph
Peter
Jane
Peter
Small worlds
Small worlds

Each ant on its own is very simple, but the y p ,
colony as a whole can work together
cooperatively to accomplish very
complex tasks, without any central control;
that is, without any ant or group of ants
being in chargebeing in charge.

A colony of army ants,
is building a bridge.is building a bridge.
… them gradually adding themselves to
the structure. Each ant is secretingthe structure. Each ant is secreting
chemicals to communicate with the
other ants, and the whole bridge is built
without any central controlwithout any central control.
this is a
“decentralized, self‐organizing system”

Another classic example of aAnother classic example of a
complex system is the brain
h d d l lHere the individual simple agents
are neuron(s)

here is an example of the kind of
complex living structure
built by termites Termite moundbuilt by termites. Termite mound.
A major focus of complex systems
is to understandis to understand…
… how individually simple agents
d l b h iproduce complex behavior
without central control?

It has often been said a city
is like a living organism inis like a living organism in
many ways, but to what
extent do cities actually
bl li i iresemble living organisms,
in the ways they are
structured, grow, scale with
size, and operate? These
and other questions form
the basis of a rapidly
growing area of complex
systems research, which
we’ll look at in detail later
in the course.

DYNAMICSDYNAMICS
The general study of how systemsg y y
change over time

Crowd dynamics
Dynamics of
stock prices

Dynamical Systems TheoryDynamical Systems Theory
The branch of mathematics of how systems change over timeThe branch of mathematics of how systems change over time
 Calculus
 Differential equations
 I d Iterated maps
 Algebraic topology
 etc.
The dynamics of a system: the manner in which the system changes
Dynamical systems theory gives us a vocabulary and set of tools for describing
dynamics

“If we knew exactly the laws of nature and the
i i f h i h i i i lsituation of the universe at the initial moment,
we could predict exactly the situation of that
same universe at a succeeding moment.
But even if it were the case that the natural laws
had no longer any secret for us, we could still only
know the initial situation approximately. If that pp y
enabled us to predict the succeeding situation
with the same approximation, that is all we
require and we should say that the phenomenonrequire, and we should say that the phenomenon
had been predicted, that it is governed by laws.
But it is not always so;
it may happen that small differences in the initial
Henri Poincaré, 1854 – 1912
it may happen that small differences in the initial
conditions produce very great ones in the final
phenomena.
A ll i th f ill dA small error in the former will produce an
enormous error in the latter.
Prediction becomes impossible...”

“Sensitive dependence on initial conditions”Sensitive dependence on initial conditions
htt // / it /d f lt/fil /i G ll /h i d th jhttp://pmm.nasa.gov/sites/default/files/imageGallery/hurricane_depth.jpg
http://www.fws.gov/sacramento/ES_Kids/Mission‐Blue‐
Butterfly/Images/mission‐blue‐butterfly_header.jpg

CHAOSCHAOS
One particular type of dynamics of a systemp yp y y
Defined as “sensitive dependence on initialDefined as sensitive dependence on initial
conditions”

Chaos in nature
Dripping faucets
Chaos in nature
Dripping faucets
Electrical circuits
Solar system orbitsSolar system orbits
Weather and climate (the “butterfly effect”)
 ( )Brain activity (EEG)
Heart activity (EKG)
Computer networksp
Population growth and dynamics
Financial data
Financial data

Deterministic chaosDeterministic chaos
“The fact that the simple and deterministic
equation [i.e., the Logistic Map] can possess
dynamical trajectories which look like some sort
of random noise has disturbing practicalof random noise has disturbing practical
implications.
This means that even if we have a simple modelThis means that, even if we have a simple model
in which all the parameters are determined
exactly, long‐term prediction is nevertheless
impossible”
Lord Robert May (b. 1936)
impossible”
(Robert May, 1976)

Lorenz discovered that a small change
in the input to a certain system of
equations resulted in a surprisingly
large change in output.large change in output.
L d R b M (b 1936)
Lord Robert May (b. 1936)

Chaos
S i l d b h i ith iti d d i iti l ditiSeemingly random behavior with sensitive dependence on initial conditions
Logistic map
A simple, completely deterministic equation that, when iterated, can display
chaos (depending on the value of R).
Deterministic chaos
Perfect prediction, a la Laplace’s deterministic “clockwork universe”, is
impossible, even in principle, if we’re looking at a chaotic system.

Universality in ChaosUniversality in Chaos
While chaotic systems are not predictable in detail, a wide class of chaotic
systems has highly predictable “universal” propertiessystems has highly predictable, universal properties.

Logistic map. Bifurcation diagram

Significance of dynamics and chaos forSignificance of dynamics and chaos for
complex systems
 Complex unpredictable behavior from simple deterministic rules Complex, unpredictable behavior from simple, deterministic rules
 Dynamics gives us a vocabulary for describing complex behavior
 There are fundamental limits to detailed prediction
 At the same time there is universality: “Order in Chaos”

a) The Newtonian picture of a physics concerned with atoms moving in the void of a spatial
container  Einstein`s general relativity ties together space, time and matter in intrinsiccontainer  Einstein s general relativity ties together space, time and matter in intrinsic
interrelationship.
b) Complex physical systems display many properties that could not have been foreseen from
id i f h i i h iconsideration of their constituents on their own.
For example, electrons moving in metals have a band structure for their energy levels. This means
that there are some ranges of energy that are accessible to them and some which are not. This is in
complete contrast to the behaviour of individual free electrons, whose energies can take any value.co p ete co t ast to t e be a ou o d dua ee e ect o s, ose e e g es ca ta e a y a ue
d) Chaos theory (cf. Gleick 1988) is the study of systems that are exquisitely sensitive to the finest
detail of their circumstances, so that the slightest change in their surroundings totally changes their
f t b h i S h t id d d th i i t l l bilit th tfuture behaviour. Such systems are widespread and their environmental vulnerability means that
they are not truly isolatable. They must, therefore, be considered holistically, in their total context.
e) Complexity theory (cf. Kauffman 1995) is concerned with the behaviour of complex systems (see ) p y y ( ) p y (
above, c) whose constituents are inter‐related in some specific way. At present in its infancy and
largely based on computer modelling, this new science has shown that systems of this kind are
capable of spontaneously generating astonishing degrees of overall pattern in their behaviour. This
h t d t th t h f l ti f th th i f d it ill i l thas suggested to some that when a proper formulation of the theory is found, it will involve not
only exchanges between constituents but also a kind of holistic pattern‐forming capability which
has been dubbed “active information” (cf. Polkinghorne 1998a).

NETWORKNETWORK
Interdisciplinary academic field which studies
complex networks such as, information
networks, biological networks, cognitive and
semantic networks, and social networks.
The field draws on theories and methods
including graph theory from mathematics, g g p y ,
statistical mechanics from physics, data
mining and information visualization from
computer science inferential modeling fromcomputer science, inferential modeling from
statistics, and social structure from sociology.
The National Research Council defines
network science as "the study of networknetwork science as "the study of network
representations of physical, biological, and
social phenomena leading to predictive
d l f h h ”
models of these phenomena”

FRACTALFRACTAL
"fractal" from the Latin fractus or "to break“
is an object or quantity that displaysis an object or quantity that displays
self‐similarity on all scales.
The geometric characterization of the simplest fractals is self similarityThe geometric characterization of the simplest fractals is self‐similarity:
the shape is made of smaller copies of itself.
The copies are similar to the whole: same shape but different size
Koch snowflake, a fractal that begins with an
il t l t i l d th l th iddl thi dequilateral triangle and then replaces the middle third
of every line segment with a pair of line segments that
form an equilateral "bump"

Rivers are good examples of natural
f l b f h i ibfractals, because of their tributary
networks (branches off branches off
branches) and their complicated winding
paths
A fractal that models the surface of a mountain

"Fractal Geometry plays
l i htwo roles. It is the
geometry of
deterministic chaos and
it can also describe the
geometry of mountains,
clouds and galaxies." ‐g
Benoit Mandelbrot

One of the more trivial
applications of fractals is theirapplications of fractals is their
visual effect. Not only do fractals
have a stunning aesthetic value,
that is they are remarkablythat is, they are remarkably
pleasing to the eye, but they also
have a way to trick the mind.
One of the largest relationships withOne of the largest relationships with
real‐life is the similarity between
fractals and objects in nature. The
resemblance many fractals and theirresemblance many fractals and their
natural counter‐parts is so large that it
cannot be overlooked. Mathematical
f l d d l lf i ilformulas are used to model self similar
natural forms. The pattern is repeated
at a large scale and patterns evolve to
mimic large scale real world objects.

Granada : Alhambra
Gl t th d l hi tGloucester, cathedral, chiostro

Plan of a non‐fractal modernist city.
Plan of unrealistically ordered fractal city

SCALING LAWSSCALING LAWS
… describe the functional relationship p
between two physical quantities that scale
ith h th i ifi t i t lwith each other over a significant interval.
… deal with the structural and functional
consequences of changes in size or
scale among otherwise similarscale among otherwise similar
structures/organisms;

Many man made and naturally occurring phenomena, including city sizes,
i d f i d h k i d di ib dincomes, word frequencies, and earthquake magnitudes, are distributed
according to a power‐law distribution.
A power‐law implies that small occurrences are extremely common, whereas
large instances are extremely rare. This regularity or 'law' is sometimes also
referred to as Zipf and sometimes Pareto. To add to the confusion, the lawsp ,
alternately refer to ranked and unranked distributions. Here we show that all
three terms, Zipf, power‐law, and Pareto, can refer to the same thing, and how
to easily move from the ranked to the unranked distributions and relate theirto easily move from the ranked to the unranked distributions and relate their
exponents.
When all aspects of the “structure” scale in a similar way the geometricWhen all aspects of the structure scale in a similar way the geometric
integrity is maintained with size (“isomorphic” or “isometric” scaling )
O th th h d if diff t l t f t ith diff tOn the other hand, if different elements of a system with different
functionalities do not scale in a similar way, the scaling is called “allometric”
scaling.

allometry l ll d bi l i lallometry, also called biological
scaling, in biology, the change in
organisms in relation to proportional
changes in body size. An example of
allometry can be seen in mammals.
Ranging from the mouse to the elephant, g g p ,
as the body gets larger, in general hearts
beat more slowly, brains get bigger, bones
get proportionally shorter and thinnerget proportionally shorter and thinner,
and life spans lengthen
Parameter X Exponent λParameter, X Exponent, λ
1 Metabolic rate 3/4
2 Lifespan 1/4
3 G h 1/43 Growth rate −1/4
4 Heart beat rate −1/4
5 Length of aorta, height of trees 1/4
6 Radii of aorta, radii of tree trunks 3/8

Living organisms obey certain very simple scaling lawsLiving organisms obey certain very simple scaling laws.
The general equation that represents the scaling behavior of living organisms
i f 21 d f it d ( ll t i b fspanning a mass range of over 21 orders of magnitude (smallest microbe of
10−13 g to the largest mammals and plants of mass 108 g) can be written as
follows (allometric scaling law):
Y Y MλY = Y0 Mλ
where Y is some observable (and quantifiable) biological parameterwhere Y is some observable (and quantifiable) biological parameter
Y0 is a normalizing constant
M is the mass of the organism, and λ is the allometric exponent

This equation happen in fractal structureThis equation happen in fractal structure
and this law are ubiquitous in nature.
In “Scaling laws in cognitive sciences” scholars have demonstrate that the
li l d l b h i l d li i i i i i i hscaling laws pervade neural, behavioral and linguistic activities suggesting the
existence of processes or patterns that are repeated across scales of analysis.
“Scaling laws in cognitive sciences” (Kello, C. T., Brown, G. D. A., Ferrer‐i‐Cancho, R., Holden, G.,
Linkenkaer‐Hansen, K., Rhodes, T. & Van Orden, G. C., 2010),

Kleiber's law,[1] named after Max Kleiber's biological work in the early 1930s,
i h b i h f h j i f i l i l' b liis the observation that, for the vast majority of animals, an animal's metabolic
rate scales to the ¾ power of the animal's mass.
Symbolically:
if q0 is the animal's metabolic rate, and M the animal's mass, then Kleiber's law
states that
q ~ M¾q0 M¾
Thus a cat, having a mass 100 times that of a mouse, will have a metabolism
roughly 31 times greater than that of a mouse. In plants, the exponent is close
to 1.

Body size versus metabolic rate for a variety of species Originally published in Kleiber (1947)
Body size versus metabolic rate for a variety of species. Originally published in Kleiber (1947).

Kleiber's law, as many other biological allometric laws, is a consequence of the
h i d f i l i l diphysics and geometry of animal circulatory systems, according to some
authors.[1][2] Young (i.e., small) organisms respire more per unit of weight
than old (large) ones of the same species because of the overhead costs of
growth, but small adults of one species respire more per unit of weight than
large adults of another species because a larger fraction of their body mass
consists of structure rather than reserve; structural mass involves maintenance;
costs, reserve mass does not.
1. West, Geoffrey; Brown, Enquist (1997). "A General Model for the Origin of Allometric Scaling
Laws in Biology". Science 276 (122).gy ( )
2. Shour, Robert (November 2012). "Entropy and its relationship to allometry". arXiv.
arXiv:0804.1924.

Scaling crime income etc with city population
Scaling crime, income, etc. with city population

If you fit a power
l th t i lilaw — that is, a line
on the above log‐
size/log‐rank plot —
you can use rank to
predict the sizes of
smaller cities very
accurately,
according to Will’s
analysis. Larger a a ys s a ge
cities are more
problematic, lying
off the lineoff the line.

ZIPF’S LAWZIPF’S LAW
An empirical law formulated using
mathematical statistics refers to the fact thatmathematical statistics, refers to the fact that
many types of data studied in the physical and
social sciences can be approximated with a
Zipfian distribution, one of a family of related
discrete power law probability distributions.
The law is named after the
American linguist George Kingsley Zipf (1902–
1950), who first proposed it (Zipf 1935, 1949)
George K. Zipf (1949) Human Behavior and the Principle of
Least Effort. Addison‐Wesley.

in probability, assertion that the frequencies f of certain events (PI) are
i l i l h i kinversely proportional to their rank r
1frequencies f
ȣ
__1__
Rank
The law was originally proposed by American linguist George Kingsley Zipf
(1902–50) for the frequency of usage of different words in the English
language; this frequency is given approximately by f(r) ≅ 0.1/r. Thus, the most
common word (rank 1) in English, which is the, occurs about one‐tenth of the
time in a typical text; the next most common word (rank 2), which is of, occurs
about one‐twentieth of the time; and so forth. Another way of looking at this is
that a rank r word occurs 1/r times as often as the most frequent word, so thethat a rank r word occurs 1/r times as often as the most frequent word, so the
rank 2 word occurs half as often as the rank 1 word, the rank 3 word one‐third
as often, the rank 4 word one‐fourth as often, and so forth. Beyond about rank
1 000 the law completely breaks down
1,000, the law completely breaks down.

The following graphs and tables compare the actual number of ‘Likes’ and
‘ ll ’ f (i bl ) i h h ‘ ik ’ d ‘ ll ’ di d b‘Follows’ for NBA teams (in blue) with the ‘Likes’ and ‘Follows’ predicted by
Zipf’s law (in red)

Distribution of City populationDistribution of City population
Linguistics
Economy
Frequency of webpages access
Income
heartquarkes
The largest cities, the most frequently used words, the income of the richest
countries, and the most wealthy billionaires, can be all described in terms of y
Zipf’s Law, a rank‐size rule capturing the relation between the frequency of a
set of objects or events and their size.

Zipf’s Law for
National Gross
Domestic Products
1900‐2008
The Gross Domestic Products of nations appear to show a more and more a Zipfian behavior over the last one hundred years. We propose a fascinating
interpretation of this evidence in terms of globalization In fact we have said that a set is Zipfian if there exists an internal coherence among its elements As theinterpretation of this evidence in terms of globalization. In fact we have said that a set is Zipfian if there exists an internal coherence among its elements. As the
world has become more fully globalized, we observe that Zipf’s Law holds for an increasing number for countries. In fact in 2000 and 2008 we observe that not
only the highest GDPs satisfy Zipf’s Law (red line) but also the top fifty economies and that the rank at which the deviation from a Zipf’s Law behavior starts
increases in time, suggesting the idea that world economic system is getting more and more coherent, i.e. globalized. Globalization is making the world fully
coherent/integrated with respect to the richness distribution among its units (i.e. countries) while this degree of integration has not yet been reached by the
world’s national populations (see Fig. 3). Sources: Wikipedia: various pages on
GDP http://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal) andhttp://en.wikipedia.org/wiki/List_of_regions_by_past_GDP_(PPP).

The investigation of phenomena involving complex geometry, patterns and scaling has
th h t l d l t i th t d d F thi l ti l h tgone through a spectacular development in the past decades. For this relatively short
time, geometrical and/or temporal scaling have been shown to represent the common
aspects of many processes occurring in an unusually diverse range of fields including
physics mathematics biology chemistry economics technology and human behaviorphysics, mathematics, biology, chemistry, economics, technology and human behavior.
As a rule, the complex nature of a phenomenon is manifested in the underlying intricate
geometry which in most of the cases can be described in terms of objects with non‐
integer (fractal) dimension In other cases the distribution of events in time or variousinteger (fractal) dimension. In other cases, the distribution of events in time or various
other quantities show specific scaling behavior, thus providing a better understanding of
the relevant factors determining the given processes. Using fractal geometry and scaling
as a language in the related theoretical, numerical and experimental investigations, itas a language in the related theoretical, numerical and experimental investigations, it
has been possible to get a deeper insight into previously intractable problems. Among
many others, a better understanding of growth phenomena, turbulence, iterative
functions, colloidal aggregation, biological pattern formation, stock markets and, gg g , g p ,
inhomogeneous materials has emerged through the application of such concepts as
scale invariance, self‐affinity and multifractality. The main challenge of the journal
devoted exclusively to the above kinds of phenomena lies in its interdisciplinary nature;
it is our commitment to bring together the most recent developments in these fields so
that a fruitful interaction of various approaches and scientific views on complex spatial
and temporal behaviors in both nature and society could take place.

Wh dWhat does
this mean?

 Existence of scale constants occurs through fractal qualities of structures
 The quarter‐power scaling law is pervasive in biology
 Organisms have evolved hierarchical branching networks that terminate in
size‐invariant units, such as capillaries, leaves, mitochondria, and oxidase
molecules.
 These design principles are independent of detailed dynamics and explicit
models and should apply to virtually all organismsmodels and should apply to virtually all organisms
Source:Source:
The Fourth Dimension of Life: Fractal Geometry and Allometric Scaling of Organisms, Geoffrey B.
West, James H. Brown, Brian J. Enquist

“In biological systems, scaling laws can reflect adaptive processes of various
d f li k d l i d i i l itypes and are often linked to complex systems poised near critical points.
The same is true for perception, memory, language and other cognitive
phenomena.
Findings of scaling laws in cognitive science are indicative of scaling invariance
in cognitive mechanisms and multiplicative interactions among interdependentg p g p
components of cognition”
Source
Scaling laws in cognitive sciences, Kello, C. T., Brown, G. D. A., Ferrer‐i‐Cancho, R., Holden, G., g g , , , , , , , , ,
Linkenkaer‐Hansen, K., Rhodes, T. & Van Orden, G. C., 2010

Existence of scaling lawsExistence of scaling laws
we can find them in our cerebral
functions, language, biological
structures, etc..
Th li k bThey represent a link between
physics, biology and psychology, and
join human species to other species
join human species to other species

fractal configuration and scale constantsfractal configuration and scale constants
concur to create
 comfortable (psychological, neurophysiologically)
 beautiful (aesthetically and harmonically) and
 highly connected environment
 support the life and furnish a deep sustainabilitypp p y

Universal distribution
of sizesof sizes

We have created Power gridsWe have created Power grids
or World‐Wide Web without
designing any particular
distribution of sizes into thedistribution of sizes into the
system.
The fact that the entire
system has evolved into this
particular inverse‐power
distribution implies that it is a
stable state.

Universal distributionUniversal distribution
 A b f l d ifi i l l b An enormous number of natural and artificial complex systems obey an
inverse‐power law distribution
 Invertebrate nervous systems, mammalian lungs, DNA sequences,
ecosystems, rivers
 Internet, incoming webpage links, electrical power grids
Source Nikos A Salingaros A universal rule for the distribution of sizes
Source. Nikos A. Salingaros, A universal rule for the distribution of sizes

Animal size distributionAnimal size distribution
 Ecosystems count the different animals and classify them according to their Ecosystems count the different animals and classify them according to their
mass
 Wh h h i i l ll i l fi d di ll l l Where the heavier animals eat smaller animals, we find discrete mall levels
 Distribution is a universal distribution
 Eliminating one level disrupt the entire ecosystem

A collection of sizesA collection of sizes
 Although different from UNIVERSAL SCALING both concepts are related Although different from UNIVERSAL SCALING, both concepts are related
through fractals
 C h h i l di Count how many components there are in a complex system, according to
their relative size — defines a distribution
 All components work together to optimize the system’s function

Correct distribution helps systemic stabilityCorrect distribution helps systemic stability
The stability of a system depends:The stability of a system depends:
 Upon the relative numbers and the distribution of sizes of its components
 on other factors such as system interconnectivity on the same level, and
among different levels

Common features
 Universal distribution = inverse‐power law (i.e. few large pieces, some
intermediate‐size pieces, many smaller pieces)
 Central quality that contributes towards sustainability in ecosystems
 Contributes stability to artificial complex systems
Universal distribution
 An enormous number of natural and artificial complex systems obey an
inverse‐power law distribution
 Invertebrate nervous systems mammalian lungs DNA sequences Invertebrate nervous systems, mammalian lungs, DNA sequences,
ecosystems, rivers
 Internet, incoming webpage links, electrical power grids

In simple terms
 Smaller design elements are more numerous than larger ones
 Their relative numbers are linked to their size: “the multiplicity of an element
(design or structural) having a certain size is inversely proportional to its
size”
 I propose that this rule applies to all adaptive design, for systemic reasons

A kind introduction to complexityA kind introduction to complexity
Alessandro Giuliani
alessandro.giuliani@iss.it
Lecture 02International Society of Biourbanism - Summer School 2014
Lecture 02

"A human being should be able to change a diaper, plan an invasion, butcher a
hog, conn a ship, design a building, write a sonnet, balance accounts, build a
wall, set a bone, comfort the dying, take orders, give orders, cooperate, acty g g p
alone, solve equations, analyze a new problem, pitch manure, program a
computer, cook a tasty meal, fight efficiently, die gallantly. Specialization is for
insects." ‐ Robert A. Heinleininsects. Robert A. Heinlein
Statistical appreciation of the data is never neutral with respect to the studiedStatistical appreciation of the data is never neutral with respect to the studied
phenomenon and implies the conscious acquiring of a specific perspective
necessitating both a global attitude and the humility to look at the details.

Pavel Florenskij points our attention to the fact
‘magicians’ shows follow a path very similar
to the foundation of ‘Scientific Truth’

Both in science and
illusionism we give for
t d th i t fgranted the existence of
shared material
experiences we do not
investigate further.

Classical Physics Statistical Mechanics Network Science

Where order starts: two alternative ideasWhere order starts: two alternative ideas
‘A la Newton’ ‘A la Boltzmann’

Mechanical approach works
when abstract thinking catches
the essential….

1. Probability. Knowing the
proportion of red beads in theproportion of red beads in the
bag, how many red beads will
show up in a sample of n beads?
2. Statistics. Knowing the number
of red beads in a sample of n
beads, what is the proportion of
red beads in the bag?
3. Process Control. Is there a bag?
Donald Wheeler, 1952.

Systemic thinking (middle‐out) is the natural way of chemical thinking
Any chemical scholar knows since his first year of course that the same
Hydrogen atom inserted in a CH4 molecule has different features with respect
to the same atom inserted in an H2O molecule (top‐down constraints) while, in
the same time the global features of a molecule derive from the costituent
atoms (bottom‐up constraints).
The relevant level is thus the relational scheme, the graph, the structural
formula.

Dmitrji Ivanovic Mendeleevj
(1834‐1907)
Relying on a discrete and finite Universe of ‘acceptable’
configurations is the trick.

A shape is kept invariant if the relations between the mutual distances of a set
f l d k i k i iof landmarks is kept invariant.
Here: 3/5 = 6/10 = 9/15…

A common (even if often misunderstood) feature of biological structures in
b h d i h f f ‘ i ili d’ fboth space and time are the presence of few ‘priviliged’ forms.
1. Around 1000 folds are sufficient to get rid of any protein structure
2. Any metazoan can be built by no more than 250 tissue types (with a very y y yp ( y
invariant gene expression profile).
3. Four basic ‘body‐plans’ (bauplan) are ate the basis of animal morphologies.
4 Four main rhytmic activities explain heartbeat dynamics4. Four main rhytmic activities explain heartbeat dynamics.
5. …
The presence of few discrete priviliged forms has important consequences on
data analysis strategies
data analysis strategies.

From a physical point of view, ‘ideal forms’
or ‘stable patterns’ can be considered as
‘attractors’ in a phase space and tell us of
the existence of some kind of (still
unknown) field in which the studied
systems are embedded.

Optimization is the core business of both science and technology

Optimization withOptimization with
multiple interacting goals
L i t d i ti di V t tLa cisterna dei carcerati di Ventotene
still working after 2000 years with no
human intervention

OptimizationOptimization
of a single
di i lmonodimensional
goalg
Dubai, Burij Khalifa
from the beginning needs to
be sustained by huge energy y g gy
injections

Traditional architecture evolved in
‘id l h ’ d t t‘ideal shapes’ correspondent to
optimal solutions to a set of
environmental constraints.
Modern architecture starts from theModern architecture starts from the
idea that the main constraints are
set by humans and in general they
collapse to economics
collapse to economics.

All these objects can be quantitatively studied by the agency
i / i i ll i b h i il i iDistance/Proximity operators allowing to compute between shapes similarities.

A shape is kept invariant if the relations between the mutual distances of a set
f l d k i k i iof landmarks is kept invariant.
Here: 3/5 = 6/10 = 9/15
Here: 3/5 = 6/10 = 9/15…

Pearson Correlation Coefficients,
lunghezza     larghezza     spessore
lunghezza        1.00000        0.97831       0.96469
l h 0 97831 1 00000 0 96057larghezza         0.97831        1.00000       0.96057
spessore          0.96469        0.96057       1.00000
Width = 19,94 + 0,605*Length

PC1 (98%) PC2 (1.4%)
Length 0,992 -0,067
Width 0,990 -0,100
Height 0,986 0,168
PC1 33 78*L th +33 73*Width + 33 57*H i htPC1= 33.78*Length +33.73*Width + 33.57*Height
PC2 = ‐1,57*Length – 2,33*Width + 3,93*Height, g , , g
The presence of an overwhelming size component explaining system varianceThe presence of an overwhelming size component explaining system variance
comes from the presence of a ‘typical’ common shape. The displacement along
pc1 corresponds to purely size variation (all positive terms), the displacement
along pc2 to shape deformation (both positive and negative terms)
along pc2 to shape deformation (both positive and negative terms).

The ‘tissue attractor’ is much stronger
th th i i di id litthan the organism individuality

ScalabilityScalability

Pearson Correlation is the basic metrics to face Complexity

Complex systems ask for
simple mathematics…simple mathematics…
complexity looks
‘complicated’ only because
scientists are trained to dealscientists are trained to deal
with simple systems that
allow for a very sophisticated
th timathematics...
(Pascal did understood that
point very well in his
distinction between ‘esprit
de finesse’ and ‘esprit de
geometrie’..…)

A network formalization can be useful only if:
1. Topology is more important than dynamics
2. The role of nodes and arcs is univocal
3. The nodes represent effective concentrations of matter and/or energyp / gy
Good networks Bad networks
Highway system City map
People working in the same office People travelling in the same train
Protein contact maps Protein Interaction NetworksProtein contact maps Protein Interaction Networks

Node degree = number of edges
connected to a node
Average Shortest Path (ASP) =
Average length of the shortest path
connecting any two nodes of the
graph.
Betweeness Centrality : Number of
shortest paths passing by a node.

Long range contacts (dashed lines) are the most crucial for ASP minimization.

The particular modular architecture of proteins allows for the optimization of
i l i i i id h l lsignal transmission inside the molecule.
ASP parameter tends to be as low as possible given the sterical hindrance.
Topology collects much more crucial information than geometry in a way
similar to an urban subway. y
The dream is to make adjacency matrix the ‘organic formulas’ of proteins.
...what about urban planning ????p g

First suggestion: Percolation and ScalabilityFirst suggestion: Percolation and Scalability

Second Suggestion: Canonical ShapesSecond Suggestion: Canonical Shapes

Third Suggestion: ResilienceThird Suggestion: Resilience
Resilience of Self‐organised and
Pl d iti Ji i WPlanned cities ‐ Jiaqiu Wang

The difference between the mathematical and the intuitive mind.
In the one the principles are palpable, but removed from ordinary use; so that
for want of habit it is difficult to turn one’s mind in that direction: but if one
turns it thither ever so little, one sees the principles fully, and one must have a
quite inaccurate mind who reasons wrongly from principles so plain that it is
almost impossible they should escape notice.p y p
But in the intuitive mind the principles are found in common use, and are
before the eyes of everybody. One has only to look, and no effort is necessary;
it is only a question of good eyesight but it must be good for the principles areit is only a question of good eyesight, but it must be good, for the principles are
so subtle and so numerous, that it is almost impossible but that some escape
notice. Now the omission of one principle leads to error; thus one must have
very clear sight to see all the principles and in the next place an accurate mindvery clear sight to see all the principles, and in the next place an accurate mind
not to draw false deductions from known principles.
All mathematicians would then be intuitive if they had clear sight, for they do
t i tl f i i l k t th d i t iti i dnot reason incorrectly from principles known to them; and intuitive minds
would be mathematical if they could turn their eyes to the principles of
mathematics to which they are unused.

The reason, therefore, that some intuitive minds are not mathematical is that
h ll h i i h i i l f h i hthey cannot at all turn their attention to the principles of mathematics. But the
reason that mathematicians are not intuitive is that they do not see what is
before them, and that, accustomed to the exact and plain principles of
mathematics, and not reasoning till they have well inspected and arranged
their principles, they are lost in matters of intuition where the principles do not
allow of such arrangement. They are scarcely seen; they are felt rather thang y y ; y
seen; there is the greatest difficulty in making them felt by those who do not of
themselves perceive them. These principles are so fine and so numerous that a
very delicate and very clear sense is needed to perceive them and to judgevery delicate and very clear sense is needed to perceive them, and to judge
rightly and justly when they are perceived, without for the most part being able
to demonstrate them in order as in mathematics; because the principles are
not known to us in the same way and because it would be an endless matter tonot known to us in the same way, and because it would be an endless matter to
undertake it. We must see the matter at once, at one glance, and not by a
process of reasoning, at least to a certain degree. And thus it is rare that
th ti i i t iti d th t f i t iti th ti imathematicians are intuitive, and that men of intuition are mathematicians,
because mathematicians wish to treat matters of intuition mathematically, and
make themselves ridiculous, wishing to begin with definitions and then with
axioms, which is not the way to proceed in this kind of reasoning.

Not that the mind does not do so, but it does it tacitly, naturally, and without
h l l f h f b d ll d l ftechnical rules; for the expression of it is beyond all men, and only a few can
feel it.
Intuitive minds, on the contrary, being thus accustomed to judge at a single
glance, are so astonished when they are presented with propositions of which
they understand nothing, and the way to which is through definitions and
axioms so sterile, and which they are not accustomed to see thus in detail, that, y ,
they are repelled and disheartened.
But dull minds are never either intuitive or mathematical.
Mathematicians who are only mathematicians have exact minds provided allMathematicians who are only mathematicians have exact minds, provided all
things are explained to them by means of definitions and axioms; otherwise
they are inaccurate and insufferable, for they are only right when the principles
are quite clearare quite clear.
And men of intuition who are only intuitive cannot have the patience to reach
to first principles of things speculative and conceptual, which they have never
i th ld d hi h lt th t f thseen in the world, and which are altogether out of the common.
Blaise Pascal (1660) Pensees.

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1932.

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