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.
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