Agent-based models provide a new, more realistic way to model an economy, allowing "you to capture the feedback loops and the dynamics of an economy in ways that traditional methods don’t,” says SFI External Professor Doyne Farmer in a PNAS article that reviews their use in science and industry.

"Using an expanding set of mathematical tools loosely termed 'complexity theory,' the study of these complex systems originated at the Santa Fe Institute," notes the article.

SFI External Professor Rob Axtell adds: "“The way that our computational approach will eventually outrun conventional analytical and numerical methods in economics and finance is by having much more supple and succinct representations of human behavior."

Read the article in PNAS (March 6, 2013)