Informatik Formalising the interpretation view of social interactions Frontiers of Complexity Science and Social Science Klaus G. Troitzsch Universität.

Informatik

Formalising the interpretation view of social interactionsFrontiers of Complexity Science and Social Science

Klaus G. TroitzschUniversität Koblenz-Landau, Germany

111/04/23 World Social Science Forum, Bergen, Norway, May 12, 2009

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Informatik

Complex systemsPhysical systems consist of

Living systems consist of

Human social systems consist of

particles which• obey natural laws• interact only in a

few different modes

• have no roles

• are not conscious of their interactions

• do not communicate

living things which• are partly

autonomous• interact in several

different modes• can play different

roles

• are only partly conscious of their roles and interactions (but not all are at all)

• communicate only in a very restricted manner (and never about counterfactuals)

human actors which• are autonomous• interact in

numerous different modes

• take on different roles even at the same time

• are conscious of their interactions and roles

• communicate in symbolic languages even about the counterfactual


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Informatik

Fields and forces

Physical particles interact with

Living things interact with

Human actors interact with

• the help of (a small number of different) forces

• fields which can change due to the movements of particles

• chemical substances and their concentration gradients

• by sounds (halfway symbolic, very restricted lexicon)

• by observing each other and predicting next moves

• by sounds and graphical symbols (symbolic, unrestricted lexicon, also referring to absent or non-existing things, e.g. unicorns and angels)

• by observing each other, predicting next moves and deriving regularities from what they observed (but they can also learn about regularities from others)


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Informatik

c

Systems of systems

a

e d

b

f

gh

i k l

j

nm

11/04/23 Klaus G. Troitzsch: Complex Systems Simulation in Sociology

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Informatik

Micro and macro level• “sociological phenomena penetrate into us by

force or at the very least by bearing down more or less heavily upon us” [Durckheim 1895]

macro cause

micro cause micro effect

macro effect

“downwardcausation”

“upwardcausation”

[Coleman 1990]

• both interpretations can be applied to physical systems

o macro cause = field, o “downward causation” = force, o micro effect = movement, o “upward causation” = field change

social systemso macro cause = “social field”, social norms, o “downward causation” = immergence, o micro effect = norm adoption, o “upward causation” = norm innovation


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Informatik

Micro and macro level• “sociological phenomena penetrate into us by

force or at the very least by bearing down more or less heavily upon us” [Durckheim 1895]

macro cause

micro cause micro effect

macro effect

“downwardcausation”

“upwardcausation”

[Coleman 1990]

• but the difference is

in physical systemso the effect of the “downward causation” is transitory, as is

the effect of the “upward causation” as there is usually no memory on either level

in social systemso the effect of the “downward causation” lasts for a long

time, it changes the state of the micro entity forever (extreme path dependence of the behaviour of humans and human systems!), as it is stored symbolically in his or her memory, and the effect of the “upward causation” also lasts for a long time, as there is a long-term memory in society (folklore, libraries, codes of law …) – and this is why we sometimse observe that “the force of law is superior to the law of force” [Pierre Saré in the opening ceremony]


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Informatik

Interactions

• the pheromone metaphor (chemical substances whose concentration gradient is observed and reacted to)

• the telepathy metaphor (agents read other agents’ memories directly)

• the message metaphor (messages do not necessarily express the “objective” internal state of the sender agent)


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Informatik

Message metaphor

• Software agents in simulations of economic or social processes should be able to exchange messages that hide or counterfeit their internal states.

• Agents need a language or symbol system for communicating.

• Symbol systems have to refer to the components of agents’ environments and to the actions agents can perform.


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Informatik

(not only B, but others, too, abstain from smoking, not only in the presence of A, but also on other occasions.)

(not only B, but others, too, abstain from crossing streets,not only in the presence of A’s car, but in most other cases.)

Immergence and second-order emergence• norm-invocation messages • motivate individual agents to change the

rules controlling their actions• if this happens often enough, “sociological phenomena

penetrate into us by force or at the very least by bearing down more or less heavily upon us” [Durckheim 1895]

• and as a consequence, these norm invocations – and the resulting behaviour – occur more and more often and become a “sociological phenomenon”


A: “I don’t like your smoking here,

B!”(B abstains from smoking in the presence of A.)

… and we have programmed something much like this in an agent-based simulation system!

A: You must not cross the streetwhen I am approaching in my car, B!

(B abstains from crossingthe street when A is approachingwith her car.)

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Informatik

CSS and policy modelling

• Agent-based modelling can also be applied to less simple scenarios:– emergence of loyalties within criminal

organisations and collusion between criminals and their victims: the example of extortion rackets

– emergence of practices in microfinance– spontaneous formation of teams according

to the skills of individual members– emergence of trust in online transactions

between sellers, intermediaries and buyers11/04/23 World Social Science Forum, Bergen, Norway, May 12, 2009

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Informatik

Can computational social science contribute to a better understanding of complex social systems?• CSS will first teach us to be modest in

our promises: the complexity of our current models is still humble as compared with the complexity of real-world social systems.

• Compared to equation-based and particle-based modelling, agent-based modelling as a tool for CSS has a better chance to progress beyond the limits of our current scientific understanding.


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Informatik

Thanks for your attention!


Informatik Formalising the interpretation view of social interactions Frontiers of Complexity Science and Social Science Klaus G. Troitzsch Universität.

Documents

social systems o macro

ofhuman social systems

world social science

o micro effect

social field

social science klaus

social norms

social processes