The Past as a Stochastic Process

David H. Wolpert, Michael H. Price, Stefani A. Crabtree, Timothy A. Kohler, Jürgen Jost, James Evans, Peter F. Stadler, Hajime Shimao, Manfred D. Laubichler

Research output: Contribution to journalArticlepeer-review

Abstract

Historical processes manifest remarkable diversity. Nevertheless, scholars have long attempted, with some success, to identify patterns and categorize historical actors and influences. 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.

Original languageEnglish (US)
Pages (from-to)134-152
Number of pages19
JournalJournal of Computer Applications in Archaeology
Volume7
Issue number1
DOIs
StatePublished - 2024

Keywords

  • Computational history
  • Historical trajectories
  • Social evolution
  • stochastic processes
  • time series data sets

ASJC Scopus subject areas

  • Archaeology
  • Archaeology
  • Computer Science Applications

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