English

The Past as a Stochastic Process

Applications 2021-12-14 v1 Machine Learning Econometrics

Abstract

Historical processes manifest remarkable diversity. Nevertheless, scholars have long attempted to identify patterns and categorize historical actors and influences with some success. A stochastic process framework provides a structured approach for the analysis of large historical datasets that allows for detection of sometimes surprising patterns, identification of relevant causal actors both endogenous and exogenous to the process, and comparison between different historical cases. The combination of data, analytical tools and the organizing theoretical framework of stochastic processes complements traditional narrative approaches in history and archaeology.

Keywords

Cite

@article{arxiv.2112.05876,
  title  = {The Past as a Stochastic Process},
  author = {David H. Wolpert and Michael H. Price and Stefani A. Crabtree and Timothy A. Kohler and Jurgen Jost and James Evans and Peter F. Stadler and Hajime Shimao and Manfred D. Laubichler},
  journal= {arXiv preprint arXiv:2112.05876},
  year   = {2021}
}

Comments

20 pages, 4 figures

R2 v1 2026-06-24T08:13:05.018Z