Modeling and Simulation

This week we discuss various kinds of modeling, as well as implementing models as simulations. In particular, we focus on agent-based models (ABMs). Guest speaker Tejas Ajit will tell you about building the March (1991) simulation in Excel.

Come to class prepared to build a model of how a person decides which stall to choose in the main bathrooms in Mandrell Hall. The model might be a lexicographic model as as in a decision tree (e.g., Step 1: Is there just one stall free? If yes, take it. If not, Step 2 ... ), or it might be a compensatory model in which all all factors are considered simultaneously, weighted by importance (e.g., the appeal of a stall is 4.7*cleanliness + 1.2*closeness to front door +3.1*having a hook to hang bag + ... ). Whatever the form of the model, you need to have the variables or factors ready. What are the criteria that a person (can by just you) uses to determine which stall to choose?

In addition be prepared to answer these questions in class:

• what is the difference between a model, a simulation and a theory?

• What are the main functions of a simulation?

Primary Readings

• Romney, A. K., Weller, S. C., & Batchelder, W. H. (1986). Culture as consensus: A theory of culture and informant accuracy. American Anthropologist, 88(2), 313-338. [pdf]

• Carley and Gasser. Computational organizational theory [pdf]

Secondary Readings

• Gilbert, N. AGENT-BASED MODELS [pdf]

• Schelling, T. C. (1971). Dynamic models of segregation†. Journal of mathematical sociology, 1(2), 143-186. [pdf]

• March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71-87. [pdf]

Exercise

• Work out the relationships/similarities in meaning between the following terms: model, theory, hypothesis, tenet, proposition, assumption, speculation, mechanism, process, premise, supposition