Distributed Agent-Based Simulation and GIS: An Experiment with the Dynamics of Social Norms

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• 关键词：Distributed agent ; based social simulation ; GIS ; D ; Mason ; ; Parallel computing ; Distributed systems ; ABM ; GIS
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：9523
• 期：1
• 页码：379-391
• 全文大小：562 KB
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• 作者单位：Nicola Lettieri (25)
  Carmine Spagnuolo (26)
  Luca Vicidomini (26)
  
  25. ISFOL, Università del Sannio, Benevento, Italy
  26. Dipartimento di Informatica, Università degli Studi di Salerno, Fisciano, Italy
  
• 丛书名：Euro-Par 2015: Parallel Processing Workshops
• ISBN：978-3-319-27308-2
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

In the last decade, the investigation of the social complexity has witnessed the rise of Computational Social Science, a research paradigm that heavily relies upon data and computation to foster our understanding of social phenomena. In this field, a key role is played by the explanatory and predictive power of agent-based social simulations that are showing to take advantage of GIS, higher number of agents and real data. We focus GIS based distibuted ABMs. We observed that the density distribution of agents, over the field, strongly impact on the overall performances. In order to better understand this issue, we analyzes three different scenarios ranging from real positioning, where the citizens are positioned according to a real dataset to a random positioning where the agent are positioned uniformly at random on the field. Results confirm our hypothesis and show that an irregular distribution of the agents over the field increases the communication overhead. We provide also an analytic analysis which, in a 2-dimensional uniform field partitioning, is affected by several parameters (which depend on the model), but is also influenced by the density distribution of agents over the field. According to the presented results, we have that uniform space partitioning strategy does not scale on GIS based ABM characterized by an irregular distribution of agents.