Computational Modeling

The availability of cheap computation has created a new way of understanding the world. Along with experiment and theory, computational modeling provides new tools for analysis, explanation and prediction. This class looks at the history of this revolution and the technology that underlies it.

We will survey a range of literature, from the skeptical to the exuberant, and make a critical evaluation of this putative paradigm shift. We will read some works of popular non-fiction, like Wolfram's A New Kind of Science and Strogatz's Sync, and use them as a starting place to delve deeper.

Topics may include finite automata, pseudo-random numbers, stochastic modeling, probability, Bayesian statistics, discrete-event simulation, chaos, self-organization, criticality, emergence, scale-free networks, self-similarity, fuzzy logic, and complexity theory.

Students will learn the skills of computational modeling, with an emphasis on discrete and stochastic models, and apply them to problems in a range of fields including engineering and the natural and social sciences. We will try to answer the question, "If this is a new kind of science, where is the new kind of engineering?"

Computational Modeling is an intermediate-level class; basic programming ability, in any language, is a prerequisite.

Class meetings: Monday and Thursday, 10 am to 11:50am

For more information, contact allen.downey@olin.edu