1. Informatik Formalising the interpretation view of social interactions Frontiers of Complexity Science and Social Science Klaus G. Troitzsch Universität Koblenz-Landau, Germany 1 13/06/2014 World Social Science Forum, Bergen, Norway, May 12, 2009

2. 2/11 Informatik Complex systems Physical systems consist ofLiving systems consist ofHuman 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 13/06/2014 World Social Science Forum, Bergen, Norway, May 12, 2009

3. 3/11 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) 13/06/2014 World Social Science Forum, Bergen, Norway, May 12, 2009

4. 4/11 Informatik c Systems of systems a ed b f g h i k l j n m 13/06/2014 Klaus G. Troitzsch: Complex Systems Simulation in Sociology

5. 5/11 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 causemicro effect macro effect downward causation upward causation [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 systems o macro cause = social field, social norms, o downward causation = immergence, o micro effect = norm adoption, o upward causation = norm innovation 13/06/2014 World Social Science Forum, Bergen, Norway, May 12, 2009

6. 6/11 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 causemicro effect macro effect downward causation upward causation [Coleman 1990] but the difference is in physical systems o 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 systems o 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] 13/06/2014 World Social Science Forum, Bergen, Norway, May 12, 2009

7. 7/11 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) 13/06/2014 World Social Science Forum, Bergen, Norway, May 12, 2009

8. 8/11 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. 13/06/2014 World Social Science Forum, Bergen, Norway, May 12, 2009

9. 9/11 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 As 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 13/06/2014 World Social Science Forum, Bergen, Norway, May 12, 2009 A: I dont 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 street when I am approaching in my car, B! (B abstains from crossing the street when A is approaching with her car.)

10. 10/11 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 buyers 13/06/2014 World Social Science Forum, Bergen, Norway, May 12, 2009

11. 11/11 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. 13/06/2014 World Social Science Forum, Bergen, Norway, May 12, 2009

12. 12/11 Informatik Thanks for your attention! 13/06/2014 World Social Science Forum, Bergen, Norway, May 12, 2009