An Adaptive Computational Network Model for Strange Loops in Political Evolution in Society

Julia Anten, Jordan Earle, Jan Treur

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

In this paper, a multi-order adaptive temporal-causal network model is introduced to model political evolution. The computational network model makes use of Hofstadter's notion of a Strange Loop and was tested and validated successfully to reflect political oscillations seen in presidential elections in the USA over time.
Original languageEnglish
Title of host publicationProceedings of the 20th International Conference on Computational Science, ICCS'20
PublisherSpringer Nature Switzerland AG
Publication statusAccepted/In press - 25 Mar 2020

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International

Cite this

Anten, J., Earle, J., & Treur, J. (Accepted/In press). An Adaptive Computational Network Model for Strange Loops in Political Evolution in Society. In Proceedings of the 20th International Conference on Computational Science, ICCS'20 (Lecture Notes in Computer Science). Springer Nature Switzerland AG.