TU Wien:Computational Social Simulation VU (Rengs)/Exam Questions SS24

Question Group GEN (General Social Simulation Questions)

1. What is the difference between top-down and bottom-up modeling techniques – and which simulation methods are top-down, which bottom-up. Give an example that shows the difference between the two approaches (also draw a sketch showing the layers, agents, interaction and direction of inference; choose a different example than sheep & wolves).

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2. What is a self-organizing system? What is stigmergy? What is an emergent phenomenon (emergence)? Which modelling techniques can simulate emergent phenomena?

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3. Why is prediction of social processes problematic - compare purely physical processes with social processes? Why did the apple not hit the ground and what does this represent – and is it relevant in the context of social simulations? Which social systems can be better predicted (e.g. with analytical methods or for longer periods) than others and why?

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4. Which four computational social simulation techniques have been presented in the lecture? Shortly describe them, including the number/meaning of agents and (especially important) also state for which kind of process/situation each technique would be suited well!

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Question Group SDM (System Dynamic Modelling Questions)

5. What is a causal loop diagram? What are feedback loops? What is the difference between the two methods? What are they good for and when would they better not be used? Give examples for positive and negative feedback loops (one each)!

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6. What is a stock and what is a flow? Give three different pairs of examples with one stock and one corresponding flow each including sketches in the notation used in the lecture! Further, give some examples of common misconceptions of stocks and flows!

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7. What is a system dynamics simulation model compared to causal loop and stock flow diagrams? How is such a system dynamics simulation developed (simple words)? What are such simulations used for? Which kind of systems/processes are they well suited to simulate?

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8. Sketch the following modes of dynamic behavior: Goal Seeking, S-shaped Growth, Oscillation, Overshoot and Collapse. For each of these, give examples of systems/processes that feature this behavior. Which of these do you think are most likely to be found in natural systems in the long run – give examples of systems and their qualitative behavior!

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9. From a system-theoretic view: What is the danger of a policy that only regards the short run? Why are complex socioeconomic systems hardly predictable (especially when seen from an SD perspective)? Give an example of a social system where the short run differs from the long run and why this is problematic!

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10. What is (are) the world model(s) (Club of Rome)? How many target variables did the world3 model have? What did the authors try to show with the model? What were there main conclusions from the models results? Was prediction of exact values a goal?

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Question Group MCS (Microsimulation, Cellular Automata and Social Networks Questions)

11. In the lecture we discussed different methodologies/approaches to (econometric) microsimulation. Name and shortly describe these different methods/approaches. Shortly explain / give an example for which kind of analysis/type of question each of the four methods is most relevant. Which of those approaches do you think is nowadays the most relevant?

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12. Which kind of elements does a microsimulation consist of? How are the transition probabilities obtained and what kind of tools and data are required for that? How are microsimulation models initialized? Where does that data come from? Btw. What is the difference between projections and forecasts?

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13. What characterizes cellular automata models? What does a cellular automata model consist of (describe)? Give an example how a simple cellular automata model might work (rules) – think of a simple 1- or 2-dimensional model.

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14. Are cellular automata useful to model social systems/processes - think of the Rumor Mill and the Voting models? What are CA models good at and is that still relevant? What are the limitations of cellular automata models?

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15. How are networks represented mathematically, which elements does that representation consist of? Describe the different characteristics that edges in a network may have (add sketches) and give examples for networks where the different characteristics matter!

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16. Explain the following network measures and how they are calculated (formulae or concise explanations): Node Degree, Characteristic Path Length, Clustering Coefficient!

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17. What are strong ties and weak ties in social networks? To whom would a person have strong ties and to whom weak ties? Why can weak ties still be important – explain and give examples! What does this have to do with network structures / small worlds?

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18. What is the small worlds phenomenon (what does it describe)? Describe the initial experiment that investigated the phenomenon! How is it connected to power-laws? Which kinds of networks are likely to show the small worlds phenomenon? How can a small worlds network form?

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Question Group ABM (Agent Based Modelling Questions)

19. What are the main modeling elements of an agent-based model (the rough common structure) and what characterizes an agent-based model? Give examples for these elements by reference to a specific ABM! How does an agent-based model differ from the other simulation models/methods that we discussed?

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20. What are agents in the context of ABM models? Further, describe the five main features that agents often have in an ABM model!

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21. What is part of the environment (the modelling element) in an ABM model? Furthermore, which different spatial topologies can be included in an ABM and for which kind of research question might each of them be relevant?

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23. Describe the simple bird-flocking model! What does this simple model show (i.e. why is it interesting for our purposes)? What are the behavior rules (micro-level behavior) of the birds and to which behavior do they lead (which macrolevel regularities)?

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24. Describe the demographic prisoner’s dilemma (DPD) from the second assignment! Describe the rules of the game and the expected dynamics – especially the differences to the regular prisoners’ dilemma (non-iterated, non-demographic).

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Question Group EXP (Simulation Experiment Questions)

25. What is the difference between conducting a proper simulation experiment and exploring a simulation model? What is an experimental setup in the context of simulations / what does it specify? What are target variables in this context?

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26. What are experimental designs with regard to computer simulations? What kind of designs did we mention in the lecture? What is a rerun and what does an experimental design have to do with the number of reruns of an experiment? Which experimental design does a basic Netlogo Behaviorspace experiment use?

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27. What is the difference between model verification and validation regarding agent-based models? Describe both shortly, then explain techniques for validation – which techniques are needed for which type of agent-based model (three types were mentioned with respect to scale)!

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28. What are the reasons for including stochastic elements included in simulations – especially agent-based models – i.e. which problems shall they counter? One the other hand, which challenges / problems arise from the stochastic influences in the model? What is necessary to alleviate these problems again?

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29. Shortly describe sensitivity analysis! Why is sensitivity analysis needed? What are the main challenges of conducting a sensitivity analysis? What is the connection between experimental designs and sensitivity analysis?

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