Simulation and SelfOrganization
Simulation and selforganization covers computational topics related to economics, ecology, and evolution. Techniques covered include differential equations, stochastic methods, and multiagent simulations.
 Mathematical models of competition, evolution, and economic activities
 Ontogeny and phylogeny
 Pattern formation and communication in biological systems
 Multiagent and intelligent agent modelling and analysis
 Techniques for largescale simulation
 Applications of selforganization to the creation of structures
 Applications of computational science to testing biological, social, and economic theories
 Organic computing
Materials
Questions
Lecture 1
 Given a collection of samples from a realworld distribution, describe how you would generate additional samples with a similar distribution.
 What is the relationship between the median and the mean of a typical income distribution.
 What is the Lorenz curve?
 What is the Gini coefficient?
 Name a reasonably good parametric approximation to income distributions.
 Describe possible sources of income inequality in an economy in which all workers are treated identically.
 Explain how competition in an economy can amplify inequality.
Lecture 2

What is the purpose of an auction?

What is a common value auction? What is a private value auction?

What is an English / Dutch / first price sealed bid / second price sealed bid auction?

What other auction is a Dutch auction equivalent to? Why?

What other auction is an English auction equivalent to? Why?

What are revenue and efficiency of auctions?

Explain common assumptions in auction theory: independence, risk neutrality, no budget constraints, symmetry, rationality

Explain how you simulate auctions in a discrete event simulation. How do you represent strategies? What kinds of strategies are possible?

What is the Nash equilibrium?

What is a repeated auction and how does it differ from a simple auction?
Lecture 3
 Explain and discuss the paper “Markets as a substitute for rationality”.
 Explain how markets select for efficiency. Describe a simple simulation demonstrating this phenomenon.
 Explain how private investment selects for efficiency and how bad investors are punished by the market.
 Explain attacks that public investment schemes may be subject to.
Lecture 4
 What is a cellular automaton?
 How are 1D, 1NN cellular automata numbered?
 What is Rule 110 and what is special about it?
 What is the 2D parity cellular automaton?
 What are the rules for Conway’s game of life?
 What is the “gossip model”? What does it model?
 How does the gossip model relate to diffusion and relaxation models?
 What is the GreenbergHastings cellular automaton?
 What is the “majority model”?
 What is Schelling’s model of segregation and what does it show? Why is it important?
Lecture 5
 Generally, what is a cellular automaton? How does it differ from other kinds of computational models?
 What classes of cellular automata do we distinguish?
 What is Hashlife?
 What is WireWorld?
 What is Langton’s Ant?
 What are selfreplicating loops? What is Evoloop?
 What is LargerThanLife?
 How can you implement Conway’s Life and its generalizations using FFT?
 What is a lattice gas cellular automaton?
Lecture 6
 Describe how differential equations can be used to model bacterial population growth.
 Describe the relationship between differential equation models and the underlying discrete, stochastic processes.
 What is logistic growth?
 For a 1D first order differential equation, what are the criteria for stability of solutions?
 Given systems of first order equations, what are the nullclines?
 What is a limit cycle?
 What are the equations for the harmonic oscillator?
 What are the equations for a real physical pendulum? What does the phase space look like?
 What does the phase space for the LotkaVolterra equations look like?
 Describe the FitzHughNagumo and the van der Pol models.
 What is a chaotic solution to a differential equation?
 Given examples of differential equations with chaotic behavior.
 What is the logistic map?
 What is the minimum dimensionality for a chaotic solution of a differential equation? difference equation?
Lecture 7
 Describe the structure of epidemic disease models using differential equations.
 What are the SIR, SIS, SIRwithbirth models?
 What is a hypercycle model?
 What is a delay differential equation? What properties do such equations commonly have?
 What is a diffusion model? How is it expressed as a partial differential equation?
 How do diffusion models relate to random walks?
 What is the relationship between the diffusion equation and the Poisson equation?
Lecture 8
 What is morphogenesis?
 What are the first stages of the morphogenesis of higher animals?
 What are the first stages of the embryogenesis of Drosophila?
 What patterns in the Drosophila embryo are laid down maternally?
 What is a reactiondiffusion network?
 Explain how reactiondiffusion reactions create equally sized segments.
 What is a Turing system?
 What is a GrayScott system?
 How can you quickly explore the parameter space of systems like Gray Scott systems?
Lecture 9
 What is a social network, and what are its components?
 What are examples of social networks? (Not just the electronic kind.)
 What is the relationship between social networks and graphs?
 What is the star graph? hypercube graph? line graph? wheel graph? barbell graph? complete graph? empty graph?
 What are walks, trails, and paths?
 What are closed walks, cycles, and tours?
 What is are geodesics, the geodesic distance, the diameter of a graph, and the eccentricity of a node?
 When is a graph connected? What are cutpoints and bridges?
 What does it mean for two graphs to be isomorphic? What is subgraph isomorphism? What is the complexity of solving these problems?
 What is a tree? a bipartite graph? a complement of a graph? a clique?
 What idea does the notion of “centrality” try to capture in a social network?
 What measures of centrality are there?
 What is structural balance?
 What is a cohesive subgroup? How can they be defined?
 What is the clustering coefficient of a node/graph?
Lecture 10
 What is a random binomial graph?
 What is the ErdösRenyi model?
 What is the model of randomly citing scientists?
 How is the BarabasiAlbert model generated?
 What is the key property of the BarabasiAlbert model?
 What kind of graphs is the BarabasiAlbert model supposed to generate?
 What is a power law?
 Does the ErdösRenyi model follow a power law?
 How is the WattsStrogatz graph generated?
 What is a small world graph?
Lecture 11
 What is the difference between correlation and causation?
 Define causation.
 Give an example where correlation between two variables exists, even though there is no causal relationship.
 Describe the steps for developing a frequentist statistical test.
 What is the difference between a Bayesian probability of a hypothesis and a frequentist pvalue?
 What is a confidence interval?
 What is 95% confidence interval for the binomial distribution? Where does this occur frequently?
 What is the ttest used for?
 What assumptions does the ttest rely on?
 What happens when the assumptions of the ttest are violated?
 What is the null hypothesis in a twosided ttest?
 What is the difference between a onesample and a twosample ttest?
 What is the MannWhitney U Test?
 Since the U Test is nonparametric, why don’t we always use it?
 Explain the parts of a box plot.
 How are the notches in a box plot computed? What do they mean?
 Explain the concept of publication bias and how it affects the interpretation of published results.
 What are bootstrap methods? When are they used?
 What is a permutation test? When is it used?
 What is crossvalidation and when is it used?