---
id: people/doyne-farmer
about:
  label: J. Doyne Farmer
  depiction: people/doyne-farmer.jpg
  depiction_credit: 'Doc Searls, Wikimedia Commons, CC BY 2.0.'
  description: >-
    American complex systems scientist, a pioneer of chaos theory and
    econophysics, who builds agent-based simulations of whole economies at
    Oxford and at Macrocosm.
  tags:
    - complexity economics
    - agent-based model
    - chaos
person:
  affiliation: University of Oxford
  role: complex systems scientist
  homepage: 'https://www.doynefarmer.com/'
relations:
  - predicate: member_of
    target: organizations/santa-fe-institute
provenance:
  origin: agent
  sources:
    - title: J. Doyne Farmer (Wikipedia)
      url: 'https://en.wikipedia.org/wiki/J._Doyne_Farmer'
    - title: 'About, J. Doyne Farmer (his own site)'
      url: 'https://www.doynefarmer.com/about'
  created: '2026-11-02'
  reviewed: '2026-11-02'
  reviewed_by: 'Claude, from the sources listed'
  status: draft
---
J. Doyne Farmer, born in Houston on 22 June 1952 and raised in Silver City, New Mexico, is an American complex systems scientist.[^1] He is Baillie Gifford Professor of Complex Systems Science at Oxford's Smith School of Enterprise and the Environment, directs the Complexity Economics programme at the Institute for New Economic Thinking at the Oxford Martin School, and is an external professor at the Santa Fe Institute.[^1]

As a graduate student at Santa Cruz he and Norman Packard formed Eudaemonic Enterprises and built the first wearable digital computer, to predict where a roulette ball would land.[^1,2] He then joined other graduate students in the Dynamical Systems Collective, whose main contribution was a method to reconstruct a chaotic system's state space from a single time series.[^1] He founded the Complex Systems Group at Los Alamos in 1988, co-founded the Prediction Company in 1991 to trade automatically on forecasts, and moved to the Santa Fe Institute in 1999, where he developed a theory of market ecology and helped found econophysics.[^1,2]

His later work at Oxford includes forecasts of technological progress from Wright's law, which ties falling costs to cumulative production, and a model with which his group predicted the effect of COVID-19 on the UK economy.[^1] He founded Macrocosm, where he is chief scientist, to scale these methods up into a simulator of the economy in which every company is present.[^1] Wikipedia quotes his aim: "We want to do for economic planning what Google maps did for traffic planning".[^1] His book Making Sense of Chaos: A Better Economics for a Better World was published by Allen Lane in April 2024.[^1]

On the wiki he is the founder of [Macrocosm](/engines/macrocosm/).