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Alea Iacta Est!
Understanding historical dynamics using Monte Carlo simulations
Xavier Rubio Campillo
xavier.rubio@bsc.es
@xrubiocampillo
@DataBeersBCN
3
Understanding human culture
Gray, R. D.; Atkinson, Q.D. (2003) "Language-tree divergence times support the
Anatolian theory of Indo-European origin." Nature 426.6965: 435-439
What data can we use?
A Data Science challenge
Pandora's box
We can do it!
Evolutionary biologists use data
with similar problems
It's another type of historical
research
We can use some of their tools
Siege warfare in XVIIIth century
Can we test this hypothesis?
"Vauban reversed the dominance of the trace italienne and
overturned the pattern of long sieges of early centuries"
Ostwald, J. (2007). Vauban under siege. Engineering efficiency and Martial Vigor in the War of the
Spanish Succession, Brill Academic.
“Data! Data! Data! I can't make bricks without clay!”
1. Formalise hypotheses
During the period 1702-1714...
H1 – The duration of sieges increased
H2 – The duration of sieges decreased
H3 – The uncertainty of sieges increased
H4 – The uncertainty of sieges decreased
2. Define a model
For each year between 1702-
1714
Sample the number of sieges
For each siege sample its
duration
Add to the mean/variance of
duration some fixed value
3. Define the prior knowledge
4. The dice are cast!
Execute the model with randomly sampled values from your
prior:
run 152112:
mean duration modifier = +1.5
variance duration modifier = -0.3
5. Approximate Bayesian Computation
Execute this algorithm for millions of runs
Store the parameters for the 1k runs with most similar output
to historical data
Results
Find your posterior
Some remarks
Long-term perspectives are needed to understand cultural
change
Data science is a revolution for understanding our past
All text and image content in this document is licensed under the Creative Commons Attribution-Share Alike 3.0 License
(unless otherwise specified). "LibreOffice" and "The Document Foundation" are registered trademarks. Their respective logos
and icons are subject to international copyright laws. The use of these therefore is subject to the trademark policy.
20
Moltes gràcies!
Xavier Rubio Campillo
xavier.rubio@bsc.es
@xrubiocampillo

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#1 DataBeersBCN - Xavier

  • 1. 1 Alea Iacta Est! Understanding historical dynamics using Monte Carlo simulations Xavier Rubio Campillo xavier.rubio@bsc.es @xrubiocampillo @DataBeersBCN
  • 2.
  • 3. 3 Understanding human culture Gray, R. D.; Atkinson, Q.D. (2003) "Language-tree divergence times support the Anatolian theory of Indo-European origin." Nature 426.6965: 435-439
  • 4. What data can we use?
  • 5. A Data Science challenge
  • 7. We can do it! Evolutionary biologists use data with similar problems It's another type of historical research We can use some of their tools
  • 8. Siege warfare in XVIIIth century
  • 9. Can we test this hypothesis? "Vauban reversed the dominance of the trace italienne and overturned the pattern of long sieges of early centuries" Ostwald, J. (2007). Vauban under siege. Engineering efficiency and Martial Vigor in the War of the Spanish Succession, Brill Academic.
  • 10. “Data! Data! Data! I can't make bricks without clay!”
  • 11. 1. Formalise hypotheses During the period 1702-1714... H1 – The duration of sieges increased H2 – The duration of sieges decreased H3 – The uncertainty of sieges increased H4 – The uncertainty of sieges decreased
  • 12. 2. Define a model For each year between 1702- 1714 Sample the number of sieges For each siege sample its duration Add to the mean/variance of duration some fixed value
  • 13. 3. Define the prior knowledge
  • 14. 4. The dice are cast! Execute the model with randomly sampled values from your prior: run 152112: mean duration modifier = +1.5 variance duration modifier = -0.3
  • 15. 5. Approximate Bayesian Computation Execute this algorithm for millions of runs Store the parameters for the 1k runs with most similar output to historical data
  • 18. Some remarks Long-term perspectives are needed to understand cultural change Data science is a revolution for understanding our past
  • 19.
  • 20. All text and image content in this document is licensed under the Creative Commons Attribution-Share Alike 3.0 License (unless otherwise specified). "LibreOffice" and "The Document Foundation" are registered trademarks. Their respective logos and icons are subject to international copyright laws. The use of these therefore is subject to the trademark policy. 20 Moltes gràcies! Xavier Rubio Campillo xavier.rubio@bsc.es @xrubiocampillo