Related Papers
Computers, Environment and Urban Systems
Key challenges in agent-based modelling for geo-spatial simulation
2008 •
Michael Batty
Agent-Based Modeling
Andrew Crooks
Agent-based modeling (ABM) is a technique that allows us to explore how the interactions of heterogeneous individuals impact on the wider behavior of social/spatial systems. In this article, we introduce ABM and its utility for studying geographical systems. We discuss how agent-based models have evolved over the last 20 years and situate the discipline within the broader arena of geographical modeling. The main properties of ABM are introduced and we discuss how models are capable of capturing and incorporating human behavior. We then discuss the steps taken in building an agent-based model and the issues of verification and validation of such models. As the focus of the article is on ABM of geographical systems, we then discuss the need for integrating geographical information into models and techniques and toolkits that allow for such integration. Once the core concepts and techniques of creating agent-based models have been introduced, we then discuss a wide range of applications of agent-based models for exploring various aspects of geographical systems. We conclude the article by outlining challenges and opportunities of ABM in understanding geographical systems and human behavior.
The Use of Agent-Based Modelling for Studying the Social and Physical Environment of Cities
Andrew Crooks
The agent-based modeling (ABM) paradigm provides a mechanism for understanding the effects of interactions of individuals and through such interactions emergent structures develop, both in the social and physical environment of cities. This chapter explores how through the use of ABM, and its linkage with complexity theory, allows one to create agent-based models for the studying cities from the bottom-up. Specifically the chapter focuses on segregation and land-use change. Furthermore, it will highlight the growing interest between geographical information systems (GIS) and ABM. This linkage is allowing modellers to create spatially explicit agent-based models, thus relating agents to actual geographical places. This approach allows one to explore the link between socio-economic geography of the city and its built physical form, and can support decision-making regarding interventions within the social and physical environment.
Complex Adaptive Systems Modeling
Complex adaptive systems modeling with Repast Simphony
2013 •
Charles Macal
PurposeThis paper is to describe development of the features and functions of Repast Simphony, the widely used, free, and open source agent-based modeling environment that builds on the Repast 3 library. Repast Simphony was designed from the ground up with a focus on well-factored abstractions. The resulting code has a modular architecture that allows individual components such as networks, logging, and time scheduling to be replaced as needed. The Repast family of agent-based modeling software has collectively been under continuous development for more than 10 years.MethodIncludes reviewing other free and open-source modeling libraries and environments as well as describing the architecture of Repast Simphony. The architectural description includes a discussion of the Simphony application framework, the core module, ReLogo, data collection, the geographical information system, visualization, freeze drying, and third party application integration.ResultsInclude a review of several R...
Transactions in GIS
The Co-evolution of Residential Segregation and the Built Environment at the Turn of the 20th Century: A Schelling Model
2014 •
Seth Spielman, Patrick Harrison
To what degree does the built environment of cities shape the social environment? In this paper we use a Schelling-like agent based model to consider how changes to the built environment of cities relate to changes in residential segregation by income and ethnicity. To develop this model we exploit insights from a high resolution historical GIS which maps 100% of the population of Newark, NJ in 1880. Newark in 1880 had a complex social landscape characterized by areas of significant social and economic segregation and areas of relative integration. We develop a Schelling model capable of reproducing these residential patterns. We use this model to explore the decentralization of housing, a specific phenomenon associated with the demise of the walking city in the late 19th century. Holding agent preferences constant, but allowing the landscape of the Schelling model to evolve in ways that reflect historical changes to the built environment produces changes to the social landscape that are also consistent with history. Our work suggests that changes in residential segregation do not necessarily imply changes to individual attitudes and preferences. Changes in residential segregation can be generated by changes to the built environment, specifically the geographic distribution of housing.
Journal of Simulation
Tutorial on agent-based modelling and simulation
2010 •
Charles Macal
Formal Languages for Computer Simulation
2014 •
Josep Casanovas
Computers, Environment and Urban Systems
Multi-agent simulator for urban segregation (MASUS): A tool to explore alternatives for promoting inclusive cities
2011 •
Flavia Feitosa
Urban segregation represents a significant barrier to achieving social inclusion in cities. To mitigate this problem, it is necessary to implement policies founded upon a better understanding of segregation dynamics. This paper proposes MASUS, a multi-agent simulator for urban segregation, which provides a virtual laboratory for exploring the impacts of different contextual mechanisms on the emergence of segregation patterns. We
Overview on agent-based social modelling and the use of formal languages
2013 •
Josep Casanovas
Computational & Mathematical Organization Theory
The Emergence of Racial Segregation in an Agent-Based Model of Residential Location: The Role of Competing Preferences
2005 •
Keith Warren
