How do we make ABM as successful as machine learning?

Invited talk at SSC2016 by Prof. Doyne Farmer, University of Oxford.


During my career machine learning has made the transition from a niche endeavor to a powerful tool used by the largest companies in the world. How do we make the same happen for ABM? I will review what I think the bottlenecks that have so far prevented ABM from realizing its full potential and discuss some ideas about how to overcome them.

Short Bio:

Prof. Doyne Farmer is Director of the Complexity Economics program at the Institute for New Economic Thinking at the Oxford Martin School, Professor in the Mathematical Institute at the University of Oxford, and anExternal Professor at the Santa Fe Institute. His current research is in economics, including agent-based modeling, financial instability and technological progress. He was a founder of Prediction Company, a quantitative automated trading firm that wassoldto the United Bank of Switzerland in 2006. His past research includes complex systems, dynamical systems theory, time series analysis and theoretical biology. During the eighties he was an Oppenheimer Fellow and the founder of the Complex Systems Group at Los Alamos National Laboratory. While a graduate student in the 70’s he build the first wearable digital computer, which was successfully used to predict the game of roulette.

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