The technique involved generating random numbers and comparing them with probabilities derived from theory. By doing this for a large number of possible neutron paths, he painstakingly painted a picture of the transport of neutrons. Fermi had, by hand, constructed the first agent-based model. These models were about to get a machine which could do these large-scale computations for them. Assembled at Los Alamos during World War II was a dream team of the great and good in science, including John von Neumann, Richard Feynman, Niels Bohr and Robert Oppenheimer. Von Neumann himself offered use of one of the first-ever computers to perform neutron calculations. That exercise culminated in the hydrogen bomb. ABMs had found their first real-world application. 11  All speeches are available online at www.bankofengland.co.uk/publications/Pages/speeches/default.aspx  11  Figure 2: John von Neumann  Figure 3: The hydrogen bomb  Source: LANL (public domain). John von Neumann in the 1940s (image available here). Source: The Official CTBTO Photostream (CC-BY-2.0). An atmospheric nuclear test conducted by the U.S. at Enewetak Atoll on 1 November 1952 (image available here). (b) Military Planning By 1947, the use of random numbers in computation had a name which reflected its probabilistic nature – 3  Monte Carlo, home of the casino. In a lecture in 1948, von Neumann described the idea of cellular automata - artificial systems of cells exhibiting life-like behaviour which evolved according to simple rules of behaviour (von Neumann et al (1966), Sarkar (2000)).
They give rise to a multiplicity of non-stationary equilibria, which evolve through time. And the resulting distribution of outcomes in this system is highly non-normal, non-linear and fat-tailed. Of course, this system is hypothetical. So it is interesting to ask whether the behaviour exhibited in real-world economic and financial systems is  Source: Kieff (CC-BY-SA-3.0-migrated-with-disclaimers). Bill Gosper’s “Glider Gun” animation created by Johan Bontes and available here. broadly consistent with the patterns from complex ABMs. One simple, reduced-form way to assess that is to look at the statistical distribution of various economic and financial time-series for evidence of discontinuity, non-normality and fat-tails. These are properties which, we know, exist in other natural and social systems (Barabasi (2005), Turrell (2013)). 19  These are: Any live cell with fewer than two live neighbours dies; Any live cell with two or three live neighbours lives on to the next generation; Any live cell with more than three live neighbours dies; Any dead cell with exactly three live neighbours becomes a live cell. 24  All speeches are available online at www.bankofengland.co.uk/publications/Pages/speeches/default.aspx  24  The short answer is yes – the properties of economic and financial systems are little different than other social, and many natural, systems (Haldane and Nelson (2012)). To provide a few illustrations, Chart 6 looks at the distribution of a set of economic and financial variables over a time-series dating back at least 150 years – equity prices, bond prices, GDP etc.