The institutional approach for modeling the evolution of human societies

Powers, Simon

Abstract

Artificial Life is concerned with understanding the dynamics of human societies. A defining feature of any human society is its institutions. However, defining exactly what an institution is has proven difficult, with authors often talking past each other. This paper presents a dynamic model of institutions, which views institutions as political game forms that generate the rules of a groups economic interactions. Unlike much prior work, the framework presented in this paper allows for the construction of explicit models of the evolution of institutional rules. It takes account of the fact that group members are likely to try to actively create institutional rules that benefit themselves at the expense of others. The paper finishes with an explicit example of how a model of the evolution of institutional rewards and punishment for promoting cooperation can be created. It is intended that this framework will allow Artificial Life researchers to address how human groups can create conditions that support cooperation. This will help to both provide a better understanding of historical human social evolution, and help in understanding the resolution of pressing public goods problems such as climate change.

Citation

Powers, S. (2016, July). The institutional approach for modeling the evolution of human societies. Presented at Artificial Life 2016

• Presentation Conference Type: Conference Paper (published)
• Conference Name: Artificial Life 2016
• Start Date: Jul 4, 2016
• End Date: Jul 8, 2016
• Acceptance Date: Mar 30, 2016
• Online Publication Date: Jul 1, 2016
• Publication Date: Jul 1, 2016
• Deposit Date: Jun 15, 2017
• Publicly Available Date: Jul 10, 2023
• Publisher: MIT Press
• Book Title: Proceedings of the Artificial Life Conference 2016
• Chapter Number: 11
• ISBN: 9780262339360
• DOI: https://doi.org/10.7551/978-0-262-33936-0-ch011
• Keywords: institutions; cooperation
• Public URL: http://researchrepository.napier.ac.uk/Output/947162