Using the Maximal Entropy Modeling Approach to Analyze the Evolution of Sedentary Agricultural Societies in Northeast China

The emergence of agriculture and the evolution of sedentary societies are among the most important processes in human history. However, although archeologists and social scientists have long been studying these processes, our understanding of them is still limited. This article focuses on the Fuxin...

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Published in:Entropy
Main Authors: Ido Wachtel, Royi Zidon, Gideon Shelach-Lavi
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2020
Subjects:
Online Access:https://doi.org/10.3390/e22030307
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spelling ftmdpi:oai:mdpi.com:/1099-4300/22/3/307/ 2023-08-20T04:02:40+02:00 Using the Maximal Entropy Modeling Approach to Analyze the Evolution of Sedentary Agricultural Societies in Northeast China Ido Wachtel Royi Zidon Gideon Shelach-Lavi 2020-03-09 application/pdf https://doi.org/10.3390/e22030307 EN eng Multidisciplinary Digital Publishing Institute Multidisciplinary Applications https://dx.doi.org/10.3390/e22030307 https://creativecommons.org/licenses/by/4.0/ Entropy; Volume 22; Issue 3; Pages: 307 maximal entropy MaxEnt northeast China locational modelling Neolithic transition to agriculture settlement patterns Text 2020 ftmdpi https://doi.org/10.3390/e22030307 2023-07-31T23:12:48Z The emergence of agriculture and the evolution of sedentary societies are among the most important processes in human history. However, although archeologists and social scientists have long been studying these processes, our understanding of them is still limited. This article focuses on the Fuxin area in present-day Liaoning province in Northeast China. A systematic archeological survey we conducted in Fuxin in recent years located sites from five successive stages of the evolution of agricultural sedentary society. We used the principles of Maximal Entropy to study changes in settlement patterns during a long-term local trajectory, from the incipient steps toward a sedentary agricultural way of life to the emergence of complex societies. Based on the detailed data collected in the field, we developed a geo-statistical model based on Maximal Entropy (MaxEnt) that characterizes the locational choices of societies during different periods. This combination of high-resolution information on the location and density of archeological remains, along with a maximal entropy-based statistical model, enabled us to chart the long-term trajectory of the interactions between human societies and their natural environment and to better understand the different stages of the transition to developed sedentary agricultural society. Text Archeological Survey MDPI Open Access Publishing Entropy 22 3 307
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic maximal entropy
MaxEnt
northeast China
locational modelling
Neolithic
transition to agriculture
settlement patterns
spellingShingle maximal entropy
MaxEnt
northeast China
locational modelling
Neolithic
transition to agriculture
settlement patterns
Ido Wachtel
Royi Zidon
Gideon Shelach-Lavi
Using the Maximal Entropy Modeling Approach to Analyze the Evolution of Sedentary Agricultural Societies in Northeast China
topic_facet maximal entropy
MaxEnt
northeast China
locational modelling
Neolithic
transition to agriculture
settlement patterns
description The emergence of agriculture and the evolution of sedentary societies are among the most important processes in human history. However, although archeologists and social scientists have long been studying these processes, our understanding of them is still limited. This article focuses on the Fuxin area in present-day Liaoning province in Northeast China. A systematic archeological survey we conducted in Fuxin in recent years located sites from five successive stages of the evolution of agricultural sedentary society. We used the principles of Maximal Entropy to study changes in settlement patterns during a long-term local trajectory, from the incipient steps toward a sedentary agricultural way of life to the emergence of complex societies. Based on the detailed data collected in the field, we developed a geo-statistical model based on Maximal Entropy (MaxEnt) that characterizes the locational choices of societies during different periods. This combination of high-resolution information on the location and density of archeological remains, along with a maximal entropy-based statistical model, enabled us to chart the long-term trajectory of the interactions between human societies and their natural environment and to better understand the different stages of the transition to developed sedentary agricultural society.
format Text
author Ido Wachtel
Royi Zidon
Gideon Shelach-Lavi
author_facet Ido Wachtel
Royi Zidon
Gideon Shelach-Lavi
author_sort Ido Wachtel
title Using the Maximal Entropy Modeling Approach to Analyze the Evolution of Sedentary Agricultural Societies in Northeast China
title_short Using the Maximal Entropy Modeling Approach to Analyze the Evolution of Sedentary Agricultural Societies in Northeast China
title_full Using the Maximal Entropy Modeling Approach to Analyze the Evolution of Sedentary Agricultural Societies in Northeast China
title_fullStr Using the Maximal Entropy Modeling Approach to Analyze the Evolution of Sedentary Agricultural Societies in Northeast China
title_full_unstemmed Using the Maximal Entropy Modeling Approach to Analyze the Evolution of Sedentary Agricultural Societies in Northeast China
title_sort using the maximal entropy modeling approach to analyze the evolution of sedentary agricultural societies in northeast china
publisher Multidisciplinary Digital Publishing Institute
publishDate 2020
url https://doi.org/10.3390/e22030307
genre Archeological Survey
genre_facet Archeological Survey
op_source Entropy; Volume 22; Issue 3; Pages: 307
op_relation Multidisciplinary Applications
https://dx.doi.org/10.3390/e22030307
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/e22030307
container_title Entropy
container_volume 22
container_issue 3
container_start_page 307
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