Transcientific Models<br><b>University of Michigan Santa Fe Institute Complexity Meeting</br></b>

Lectures and Speakers:
"Symmetry Breaking in Nature and Society," Simon DeDeo (Santa Fe Institute)
"Ensemble Kalman Filter," Steven Schieff (Penn State University)
"Random Chemistry Models," Maggie Eppstein (University of Vermont)
"Diffusion Limited Aggregation," Len Sander (University of Michigan)
"Adaptive and Inferential Dynamics," David Krakauer (Santa Fe Institute)
"A Model of Pair Formation," Seth Marvel (University of Michigan
"Computing Tipping Points for Contagion Models," Carl Simon (University of Michigan)

I believe we are entering a period of transcience, where it is becoming necessary that training in areas with fundamental mathematical, computational, and logical principles should be emancipated from a single class of historically contingent case studies.
– David C Krakauer

Transcientific models, such as network models, produce insights that advance scientific inquiry in multiple disciplines. For example, Sander and Witten’s model of diffusion limited aggregation, a physics model, has been applied to city formation, and replicator dynamics, which were developed to capture evolution, have proven useful models of learning.

In this single day event, a collection of leading complexity scholars will describe their favorite transcientific models and explain how and why these models leapt their original disciplines. All presentations will begin with jargon free model descriptions accessible to a general audience and conclude with an open discussion about possible other applications.

The event will consist of a morning session from 9am-noon and an afternoon session from 1-5 pm with a break for lunch.