Neuroergonomics and sociogenesis, Lectures part 1

i d i iNeuroergonomics and sociogenesis

Internationa Society of BiourbanismSummer School 2014

bi b i i f @bi b iwww.biourbanism.org ‐ [email protected]

Biourbanism ManifestoAntonio 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 yand 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 connectedwhole 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 commonmethodology, but also in the content of the results (hence the prefix “Bio”), because the city represents the living environment of thehuman species. Biourbanism recognizes “optimal forms” defined at different scales (from the purely physiological up to the ecologicallevels) which, through morphogenetic processes, guarantee an optimum of systemic efficiency and for the quality of life of thei 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’sevolution, 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 peopleexpress 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 ofDeep Ecology (Bateson) on social‐environmental grounds; (ii) the identification and actualization of environmental enhancementaccording 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 fueleconomy towards a new organizational model of civilization; and (iv) deepening the organic interaction between cultural and physicalfactors 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 yCresskill, 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.

iNeuroergonomicsurban designurban designsociogenesisgby 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 inArtena, Italy, on July 13th‐20th 2014. The program offers seven full days of lectures, practical workshops, and design studios, withinternational experts for exploring how to design urban environments able to revive, support, nourish, and enhance sociality andhuman relationships. Seven additional days will be devoted to study the ancient urban codes of two biophilic Italian towns, Artenaand 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 theinternationalWorkshop 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. Spacebecomes place when intentionality is at stake, and landscape, nature, buildings, and forms in space have a meaningful interactionwith 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 urbanenvironment 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 schoolaims 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, environmentalpsychology, 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 gin 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 prerequisiteto urban planning (Neuroergonomics and UrbanDesign, 2012), followed by its small‐scale applicationsfor propagating systemic effects over the entirefor propagating systemic effects over the entireurban organism through biourban acupuncture(Neuroergonomics and urban placemaking, 2013),participants in the 2014 International Summer Schoolin Biourbanism will focus on how to design spacesthat facilitate and reinforce social relations with athat facilitate and reinforce social relations, with aspecial program in neuroergonomics andsociogenesis.

This issue is of paramount importance becausealthough modern cities gather millions of people in,they tend to overlook and break down humanrelations, as Marx and Engels already noticed almosta century and a half ago.[1] This decade, cities havebecome the living environment for half of thegplanet’s population for the first time in history, andaccording to urban migration and growth trends, 64%and 86% of the developing and developed worldrespectively 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] whileurban exploitation of land will double in less than 20years.[3]What kind of design is behind such anenvironmentally unsustainable, speedy, andd 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 Corbusierof 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 thehorizon of human life according to production. And that’s precisely why they break social connections. In a way, the early subsidiaryand social role of cities has been morphed into the capitalistic subsumption[6] device par excellence. This happened by firstlytransforming 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, andturned dwellings into individualistic boxes, piled into suburbia. This has allowed less and less room for delightfulness and socialconnections, 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 isheading towards a dematerialization of places.

As we know, space has become almost irrelevant for producing surplus value thanks to the deployment of information technologyand its global dominance. Smart cities of today – the citadels of global capitalism – don’t need to destroy places anymore, becausefinance 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 lossof human connection to reality (i.e. nature, other human beings, and themselves) has been outlined by Ivan Illich.[9] Telephoney ( , g , ) y [ ] pdevices, Internet, and social media seem to widen the range of sociability, while on the contrary they’re actively regimenting it. Themedium is the message as notoriously McLuhan put it; and the message shapes and steers the messenger towards the purpose forwhich the medium was built. So to speak, what we write down on Twitter is Twitter itself. A self‐referential production andconsumption of a stream of information may be amusing, but it in fact happens in physical solitude and distracts awareness and lifefrom 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 wereally see going through a coded and engineered human settlement is, instead, a forest of abstract signs referring to its hyperrealbackbone – 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 ofnature, through human consumerism), according to the evolution of our society. Paraphrasing Bertrand Russell, one could say thatplace 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 lifewithin a physical and cultural horizon that deflects social intentionality into passive cattle‐like individualism. “Non‐freedom” is not ablatant dictatorship, as placelessness is not a horrific instantiation of chaos. It rather occupies subtly the imaginary for eliciting andcontrolling 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 intheir neat, efficiently fancy urban organization and architecture.

Given that real human connection doesn’t consist ofh tti b t d d f h ichatting about ready‐made news nor of havingdrinks together, everyone notices how it isobjectively difficult to cultivate authentic sociabilityin the rushing routine that our lives turned out tobe. A real interest towards the other, solidarity, evenconflict, and in the end truth, are being banished byour urban society, as they have become irrelevantfor our Hobbesian vision of the world.

Nevertheless on the other hand dematerializationNevertheless, on the other hand, dematerializationis setting free many urban places, especially wherethe system controls fail, i.e. where raw physics andbiology matter. Human reactions flourish like weedsbetween the cracks, in the scarce interstices whereth ’ littl f f lthere’s little or no room for performance, goals,possession – and thus subsumption plugs can’twork.[12] Locality is furthermore living a new dawn,and it’s showing its ability to counter‐exploit theglobal 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 practitionersdebate. 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 ofMonotowns 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 thatpositively 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 ofmodern 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 – thesubjects that biourbanism connects together for offering a new vision over urban studies. The human attitude towards the aliveworld, 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 gdesign with human biological and psycho‐neuro‐immunological wellness. It scientifically upholds the call for a human‐centred designby 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 andwell‐working according to context, human feeling, the material and social needs of the time. That has nothing to do with stylisticnostalgia 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 distinguishedexpert in Mediterranean urban codes. He devoted more than 40 years of research studying why Mediterranean cities from the 6th tothe 19thcenturies AD are so beautiful and well fitting. His work showed the existence of bottom‐up urban codes, based on socialconnections and commons, rather than on a formal top‐down blueprint envisioned by an architect. Ancient Mediterranean townsunfolded outwards according to proscriptive, local, shared rules that were understandable and enforceable by everyone, and thatformed 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 interestingproperties from the biourbanism point of view: the urban forms generated through such a process share fractal and biophilicqualities 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 specificdynamics 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 thesubject. The project will have a dynamic character, because sociogenesis never reaches an end. Like a living body, it is constantlyadapting to changes. The product of socio‐generative design is therefore a system, not merely a structure. It includes a proceduralhomeostatic 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 itsaffordances, 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, willsleep in their houses, eat and work in the same vibrant and real set they are going to study, because knowledge is not about readingor talking, but primarily about experiencing, feeling, observing, and doing. One must be humble when seeking for the reality to openup.

After the ISB summer school, Professor Hakim will lead a research project on local codes (Artena, Segni) from July 21st to 27th Weexpect 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 theAutonomous 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 summerschool 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 SourceLogistics, Beyond Economics, and Biophilia/Design and Power), a sensory seminar, a site‐specific design studio and field trips. Mostrelevant will be the space given to Peer‐to‐peer Urbanism as a participatory urban planning approach to design, construct, and repaircities in a way that anyone may choose: participate, share, and modify theories, methods, and implementation technologies at anytime. 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 contradictand negate the current economic restructuring regime. A new urban design is needed for building authentic cities – polis – able tobring 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 1969http://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. PenguinClassics: London 1990 pp. 943–1084.[7] Nikos Salingaros. Complexity and Urban Coherence. Journal of Urban Design, vol. 5 (2000), pp. 291‐316http://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.) GeographicInformation 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 NeilPostman, 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 ofSocial Innovation. 2013 http://macromesomicro.com/book/[14] See for example Besim Hakim, “Mediterranean urban and building codes: origins, content, impact, and lessons”, Urban DesignInternational, 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 Designtheoretical key conceptstheoretical key concepts

Antonio Caperna, [email protected]

Lecture 01International Society of Biourbanism - Summer School 2014

Lecture 01

Key wordsKey words

biourbanism homologyevolutionary biology architecture

b iurbanism biophilic designmorphogenetic 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 partsPhenomena 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 eseparated 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 approachWhat 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".

complexitymay 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 complexityIn 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 psystems.


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 tsconnected 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

SarahRalph

Peter

Jane

Peter

Small worldsInternational Society of Biourbanism - Summer School 2014

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 structurebuilt 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 ychange 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 yenabled 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 orbitsSolar 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)

ChaosS i l d b h i ith iti d d i iti l ditiSeemingly random behavior with sensitive dependence on initial conditions

Logistic mapA simple, completely deterministic equation that, when iterated, can display chaos (depending on the value of R).

Deterministic chaosPerfect 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 spatialcontainer Einstein`s general relativity ties together space, time and matter in intrinsiccontainer Einstein s general relativity ties together space, time and matter in intrinsicinterrelationship.

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).


NETWORKNETWORKInterdisciplinary 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 distributedaccording to a power‐law distribution.

A power‐law implies that small occurrences are extremely common, whereaslarge instances are extremely rare. This regularity or 'law' is sometimes alsoreferred to as Zipf and sometimes Pareto. To add to the confusion, the lawsp ,alternately refer to ranked and unranked distributions. Here we show that allthree terms, Zipf, power‐law, and Pareto, can refer to the same thing, and howto easily move from the ranked to the unranked distributions and relate theirto easily move from the ranked to the unranked distributions and relate theirexponents.

When all aspects of the “structure” scale in a similar way the geometricWhen all aspects of the structure scale in a similar way the geometricintegrity 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 differentfunctionalities 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, λ1 Metabolic rate 3/42 Lifespan 1/43 G h 1/43 Growth rate −1/44 Heart beat rate −1/45 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 parameterY0 is a normalizing constantM 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 M¾Thus 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 theh 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 weightthan old (large) ones of the same species because of the overhead costs ofgrowth, but small adults of one species respire more per unit of weight thanlarge adults of another species because a larger fraction of their body massconsists 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 gecities are more problematic, lying off the lineoff the line.


ZIPF’S LAWZIPF’S LAWAn 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) arei 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 yZipf’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 hasth 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 commonaspects of many processes occurring in an unusually diverse range of fields includingphysics 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 intricategeometry 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 variousother quantities show specific scaling behavior, thus providing a better understanding ofthe relevant factors determining the given processes. Using fractal geometry and scalingas a language in the related theoretical, numerical and experimental investigations, itas a language in the related theoretical, numerical and experimental investigations, ithas been possible to get a deeper insight into previously intractable problems. Amongmany others, a better understanding of growth phenomena, turbulence, iterativefunctions, colloidal aggregation, biological pattern formation, stock markets and, gg g , g p ,inhomogeneous materials has emerged through the application of such concepts asscale invariance, self‐affinity and multifractality. The main challenge of the journaldevoted 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 sothat a fruitful interaction of various approaches and scientific views on complex spatialand 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 oxidasemolecules.

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 variousd 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 cognitivephenomena.

Findings of scaling laws in cognitive science are indicative of scaling invariancein cognitive mechanisms and multiplicative interactions among interdependentg p g pcomponents of cognition”

SourceScaling 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 entiresystem has evolved into thisparticular inverse‐powerdistribution implies that it is astable 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 [email protected]

Lecture 02International Society of Biourbanism - Summer School 2014

Lecture 02

"A human being should be able to change a diaper, plan an invasion, butcher ahog, conn a ship, design a building, write a sonnet, balance accounts, build awall, set a bone, comfort the dying, take orders, give orders, cooperate, acty g g palone, solve equations, analyze a new problem, pitch manure, program acomputer, cook a tasty meal, fight efficiently, die gallantly. Specialization is forinsects." ‐ 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 studiedphenomenon and implies the conscious acquiring of a specific perspectivenecessitating 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 workswhen 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 sameHydrogen atom inserted in a CH4 molecule has different features with respectto the same atom inserted in an H2O molecule (top‐down constraints) while, inthe same time the global features of a molecule derive from the costituentatoms (bottom‐up constraints).

The relevant level is thus the relational scheme, the graph, the structuralformula.


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 gyinjections


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 0.96469l h 0 97831 1 00000 0 96057larghezza 0.97831 1.00000 0.96057spessore 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 strongerth 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 mapPeople working in the same office People travelling in the same trainProtein 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 thatfor want of habit it is difficult to turn one’s mind in that direction: but if oneturns it thither ever so little, one sees the principles fully, and one must have aquite inaccurate mind who reasons wrongly from principles so plain that it isalmost impossible they should escape notice.p y pBut in the intuitive mind the principles are found in common use, and arebefore 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 areso subtle and so numerous, that it is almost impossible but that some escapenotice. Now the omission of one principle leads to error; thus one must havevery 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 mindnot 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 mindswould be mathematical if they could turn their eyes to the principles ofmathematics to which they are unused.


The reason, therefore, that some intuitive minds are not mathematical is thath ll h i i h i i l f h i hthey cannot at all turn their attention to the principles of mathematics. But thereason that mathematicians are not intuitive is that they do not see what isbefore them, and that, accustomed to the exact and plain principles ofmathematics, and not reasoning till they have well inspected and arrangedtheir principles, they are lost in matters of intuition where the principles do notallow of such arrangement. They are scarcely seen; they are felt rather thang y y ; yseen; there is the greatest difficulty in making them felt by those who do not ofthemselves perceive them. These principles are so fine and so numerous that avery 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 judgerightly and justly when they are perceived, without for the most part being ableto demonstrate them in order as in mathematics; because the principles arenot 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 toundertake it. We must see the matter at once, at one glance, and not by aprocess 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, andmake 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 withouth 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 singleglance, are so astonished when they are presented with propositions of whichthey understand nothing, and the way to which is through definitions andaxioms 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 allthings are explained to them by means of definitions and axioms; otherwisethey are inaccurate and insufferable, for they are only right when the principlesare quite clearare quite clear.And men of intuition who are only intuitive cannot have the patience to reachto 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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Neuroergonomics and sociogenesis, Lectures part 1

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