Description

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This book offers a first step towards getting machines to understand history in terms of analysing historical narratives. It uses computational intelligence and history texts as keys to ask different questions than have been asked about our human history so far.

The book is divided into three main parts. The first part discusses the mathematical language of history, the second part uses simple models to analyse historical laws written in mathematical language, and the third part discusses the impact of general Large Language Models (LLMs) on the study of history. Contents

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Front Matter
The Mathematical Language of Digital History
Front Matter
Asymptotics in Digital Humanities
Function Diagrams in Digital Humanities
History of War
History Through Clocks
Networks and Macrohistory
Networks and Microhistory
Metahistory: Computational Models for History
Front Matter
What Is a Computational Model for History
History Through the Core
History After the Death of the Witnesses
History While the Witnesses Are Still Alive
Propaganda in History
Stochastic Terrorism
Historian Machine
History Through AI
Front Matter
Information and History
Machine Learning and History
Representing Historical Information
Expert System in History
Analyzing History with Video
Fake History
Back Matter Related Topics

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Applied Mathematics, Social Sciences