Organized complexity

I501 – Introduction to Informatics

[email protected]://informatics.indiana.edu/jbollen/I501

Informatics and computing

Lecture 4 – Fall 2009

Organized complexity





Papers:

Lazebnik, Y [2002]. "Can a biologist fix a radio?--Or, what I learned while studying apoptosis". Cancer Cell, 2(3):179-182.

Simon, H.A. [1962]. "The Architecture of Complexity". Proceedings of the American Philosophical Society, 106: pp. 467-482.

Klir, G.J. [2001]. Facets of systems Science. Springer. Chapters: 3, 8, and 11.

This week’s discussion





Systems movement Roots:

Mathematics Computer Technology Systems Thinking

Cybernetics Functional equivalence Communication and information Complexity Interdisciplinary outlook Bio-inspired mathematics and computing Computing/Mechanism-inspired biology and social

science

1965: Society for the Advancement of General Systems Theory

Ludwig von Bertalanffy

Anatol Rapoport

RalphGerard

KennethBoulding





Warren Weaver’s classes of systems and problems

Organized simplicity Classical mathematical tools Calculus and differential equations Problems with a very small number of

components With perfectly predicted behavior Deterministic

Disorganized complexity Statistical tools Very large number of components High degree of unpredictability Randomness

Organized complexity Sizable number of components which are

interrelated into an organic whole Study of organization Systems where whole is more than sum of parts Need for new mathematical and computational

tools

Organizedsimplicity

Disorganized complexity

Organized Complexity

Complexity

Rand

omne

ss

Weaver, W (1948) Science and Complexity, American Scientist, 36: 536 (1948).





Examples

Organizedsimplicity



Complexity

Rand

omne

ss





From systems science to informatics

organized complexity study of organization

“Whole is more than sum of parts” Systemhood properties Holism vs. Reductionism

Need for new mathematical and computational tools Massive combinatorial searches Problems that can only be tackled with computers Computer as lab

Understanding function Of wholes

Systems biology Evolutionary thinking

Systems thinking Emergence: How do elements combine to form new

unities?

Organizedsimplicity



Complexity

Rand

omne

ss





Models of organized complexity Systemhood properties

Search for a language of generalized circuits Isomorphy of concepts, laws and models Minimize duplication of efforts across fields Unity of science

Not mathematics. Kenneth Boulding: “in a sense, because mathematics contains all theories it contains none; it is the

language of theory, but it does not give us the content” “body of systematic theoretical construction which will discuss general relationships

of the empirical World”. “somewhere between the specific that has no meaning and the general that has no

content there must be, for each purpose an at each level of abstraction, an optimum degree of generality”.

Empirical and problem-driven Other relevant areas

Cybernetics and Information theory (Shannon and Weaver) Mathematical theories of control and generalized circuits Optimal scheduling and resource allocation (operations research)

Ludwig von Bertalanffy

KennethBoulding

Boulding's 1st Law: "Anything that exists is possible."





“Two-dimensional science” Science in the post-industrial age

Industrial society One-dimensional science

Organized simplicity and disorganized complexity Thinghood-driven, reductionist

Information society Two-dimensional science

Thinghood and systemhood Integration of empirical science with general systems Problem-driven, understanding function Understanding of levels of generality

Historical sequence of societies: Pre-industrial: “extractive” industries, manual labor, mining, low energy

density Industrial: large-scale production, machine technology Information: computational technology and trades, information

processing, services Man -> machine -> computer

George Klir





Stepping back a bit: information, what is it?

SIGN

Thing

ICON





Stepping back a bit: information, what is it?

“Information is that which reduces uncertainty”. (Claude Shannon)“Information is that which changes us”. (Gregory Bateson)“Information is a semantic chameleon”. (Rene Thom)

The word information derives from the Latin informare in + formare = give form, shape, or character to. It is therefore to be the formative principle of, or to imbue with some specific character or quality.From: Von Bayer, H.C. [2004]. Information: The New Language of Science. Harvard University Press., Chapter 3, pp 20-21.\





Systems science: cross-disciplinary For hundreds of years, the word information has been used to signify knowledge

and related terms such as meaning, instruction, communication, representation, signs, symbols, etc.

“the action of informing; formation or molding of the mind or character, training, instruction, teaching; communication of instructive knowledge”. Oxford English Dictionary

Two of the most outstanding achievements of science in the XX century Invention of Digital Computers and Information Technology Birth of Molecular Biology

Resulted in the generation of vast amounts of data and information and new understandings of the concept of information itself

Modern science is unraveling the nature of information in numerous areas such as communication theory, biology, neuroscience, cognitive science, and education, among others.

Organization very tied to idea of information Essential for systems approaches Cf. Rosen’s comments on energy vs. communication





Information as representation We often presume that such and such information is simply a factual

representation of reality but representation of reality to whom? The act of representing something as a piece of knowledge demands

the existence of a separation between the thing being represented and the representation of the thing for somebody – between the known and the knower.

This is a form of communication: the representation of an object communicates the existence of the

(known) object to the knower that recognizes the representation.





Information as representation Signs are objects whose function is to be about other things

Objects whose function is reference rather than presence. Do not deliver things but a sense or knowledge of things – a

message. Example: Road Signs

Not a distant thing; but about distant things For information to work

There has to be a system of signs Recognizable by the relevant group of people (drivers!)





Information as relation The central structure of information is a relation

among signs, objects or things, and agents capable of understanding (or decoding) the signs.

Agents are informed by a Sign about some Thing.

sign

agentsthing





Information as relation The information relation is a sign system Semiotics is the discipline that studies sign systems

sign

agentsthing





Playing with sign systems Language and sign systems surround us

We are often not aware we use them We notice them when an object oscillates between sign and thing

Reverts from reference to presence Playing with reference in sign systems is common in Art

“beware: Cliff”Or“beware: low gravity”?





Playing with sign systems

Symbols are used as pictorial objects to draw the picture of Kitty: presence

But within the silhouette of Kitty there is also a tale of cats: reference

K itty O I am my own way of being in view and yet invisible at once Hearing everything you see I see all of whatever you can have heard even inside the deep silences of black silhouettes like these images of furry surfaces darkly playing cat and mouse with your doubts about whether other minds can ever be drawn from hiding and made to be heard in inferred language I can speak only in your voice Are you done with my shadow That thread of dark word can all run out now and end our tale

by John Hollander. Kitty, Black domestic shorthair





The name of the rose

Movie version of the Umberto Eco’s book An old manuscript, the message, is

literarily dangerous Becomes literally poisonous reference and presence become

very intertwined indeed!





Play on reference The accepted meaning of the symbols

conflicts with the object Highlights how arbitrary symbols are

The Key of Dreams, 1930, Rene Maggritte

“This is not a pipe”





When is an object a sign or a thing?





Semiotics and informatics Semantics

the content or meaning of the Sign of a Thing for an Agent Relations between signs and objects for an agent the study of meaning.

Syntax the characteristics of signs and symbols devoid of meaning

Relations among signs such as their rules of operation, production, storage, and manipulation.

Pragmatics the context of signs and repercussions of sign-systems in an

environment it studies how context influences the interpretation of signs

and how well a signs-system represents some aspect of the environment

info

rmat

ion

infro

mat

ics





(Peirce’s) Typology of Signs Icons are direct representations of objects.

Similar to the thing they represent. Pictorial road signs, scale models, computer icons.

A footprint on the sand is an icon of a foot. Common in computer interface (watch the evil

metaphore!)





(Peirce’s) Typology of Signs Indices are indirect representations of objects, but necessarily

related. Smoke is an index of fire, the bell is an index of the tolling

stroke a footprint is an index of a person.





(Peirce’s) Typology of Signs Symbols are arbitrary representations of objects

Require exclusively a social convention to be understood Convention establishes a code, agreed by a group of agents, for

understanding (decoding) the information contained in symbols. Smoke is an index of fire, but if we agree on an appropriate code

(e.g. Morse code) we can use smoke signals to communicate symbolically.

Internally consistent coding + indices: ~ non-arbitrary symbols





(Peirce’s) Typology of Signs Icons are direct representations of objects.

Similar to the thing they represent. Pictorial road signs, scale models, computer icons.

A footprint on the sand is an icon of a foot. Indices are indirect representations of objects, but necessarily related.

Smoke is an index of fire, the bell is an index of the tolling stroke a footprint is an index of a person.

Symbols are arbitrary representations of objects Require exclusively a social convention to be understood

Convention establishes a code, agreed by a group of agents, for understanding (decoding) the information contained in symbols.

Smoke is an index of fire, but if we agree on an appropriate code (e.g. Morse code) we can use smoke signals to communicate symbolically.





Assignment: Blackbox I-http://www.cs.indiana.edu/~jbollen/blackboxI501/BlackBox.html-Due on October 21, 2009 (16:00 EDT)-Deliver to OnCourse folder-Deliverable: report on your findings with regards to quadrants 2 and 3

- Describe observations, collect data from online applet- Formulate hypotheses with regards to underlying algorithm- Verify/falsify hypotheses by means of data analysis

Quadrant 2

Quadrant 3

http://www.cs.indiana.edu/~jbollen/blackboxI501/BlackBox.html





Discussion questions Lazebnik, Y [2002]. "Can a biologist fix a radio?--Or, what I

learned while studying apoptosis". Cancer Cell, 2(3):179-182. Lazebnik seems to omit one important distinction between engineers and scientists. How does it affect his argument?

Simon, H.A. [1962]. "The Architecture of Complexity". Proceedings of the American Philosophical Society, 106: pp. 467-482.

Simon discusses the issue of hierarchic span. What kind of effect could the internet and modern communication systems have on the span/broadness of social systems?

Klir, G.J. [2001]. Facets of systems Science. Springer. Chapters: 3, 8, and 11.

Klir discusses Bremermann’s limit: can you think of ways of computing that would alter this limit?





Next class

Aleksander, I. [2002]. “Understanding Information Bit by Bit”. In: It must be beautiful : great equations of modern science. G. Farmelo (Ed.), Granta, London.

Rosvall, M and Bergstrom, C (2007) Maps of random walks on complex networks reveal community structure. PNAS January 29, 2008 vol. 105 no. 4 1118-1123

Organized complexity

Documents

Transcript of Organized complexity