The checkerboard model of social interaction

Sakoda, James M.

doi:10.1080/0022250x.1971.9989791

Cited by 191 publications

(125 citation statements)

References 2 publications

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“…Theoretical applications include social emergence (Sawyer, 2005), the emergence of cooperation (Axelrod, 1997), the generation of social instability (Epstein, 2002), and the collective behaviour of people in crowds (Pan et al, 2007). Sakoda (1971) formulated one of the first social agent-based models, the Checkerboard Model, which relied on a cellular automaton. Using a similar approach, Schelling developed a model of housing segregation in which agents represent homeowners and neighbours, and agent interactions represent agents' perceptions of their neighbours (Schelling, 1978).…”

Section: Applications Overviewmentioning

confidence: 99%

Tutorial on agent-based modelling and simulation

Macal

North

2010

Journal of Simulation

1,261

630

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Agent-based modelling and simulation (ABMS) is a relatively new approach to modelling systems composed of autonomous, interacting agents. Agent-based modelling is a way to model the dynamics of complex systems and complex adaptive systems. Such systems often self-organize themselves and create emergent order. Agent-based models also include models of behaviour (human or otherwise) and are used to observe the collective effects of agent behaviours and interactions. The development of agent modelling tools, the availability of micro-data, and advances in computation have made possible a growing number of agent-based applications across a variety of domains and disciplines. This article provides a brief introduction to ABMS, illustrates the main concepts and foundations, discusses some recent applications across a variety of disciplines, and identifies methods and toolkits for developing agent models.

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Section: Applications Overviewmentioning

confidence: 99%

Tutorial on agent-based modelling and simulation

Macal

North

2010

Journal of Simulation

1,261

630

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“…Cells are pixellike, same sized, and uniform in spatial configuration, for example, in models by Sakoda (1971) and Schelling (1969;1978). The models are formed in a basic checkerboard fashion, without consideration of real urban land parcels.…”

Section: The Methodsological Importance Of Geographymentioning

confidence: 99%

“…CA models of residential dynamics have also treated cell-state characteristics simply, with households represented as simple black-and-white states with a binary contentment state, for example, in the Sakoda (1971) and Schelling (1969;1978) schemes. The intention, in those models, is to abstract characteristics of households that might help to explain sociospatial segregation.…”

Section: The Methodsological Importance Of Geographymentioning

confidence: 99%

“…Relationships between cell-based households are expressed in terms of contentment regarding collocation in local spaces in segregation models (Sakoda, 1971;Schelling, 1971). Once again, these models are designed to be simple.…”

Section: The Methodsological Importance Of Geographymentioning

confidence: 99%

“…Moreover, GA relate closely to complex adaptive systems in the consideration of their interactive dynamics. The flexibility of the approach allows for the nesting of entities and their relationships across scales, and facilitates the emergence of novel spatial ensembles across those boundaries (Sakoda, 1971;Schelling, 1978), who modeled sociospatial segregation in residential location behavior with the use of basic checkerboard models. CA models of local-scale relocation have also been developed by Batty (2001) and Schweitzer (2003).…”

Section: The Methodsological Importance Of Geographymentioning

confidence: 99%

See 2 more Smart Citations

A Geographic Automata Model of Residential Mobility

Torrens

2007

Environ Plann B Plann Des

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In this paper is described a model of residential mobility, built to simulate individual households, their perception of and reaction to varying conditions across different scales of interaction, and their movements to occupy housing in a physical, social, and economic environment. The methodology underpinning the model is based on an automata core, which leverages the advantages it offers in terms of representing individual entities and their rule-based interactions. This methodology is extended, however, to incorporate geography-specific functionality, with advantages for the modeling of human systems. The applicability of the methodology is demonstrated through the development of a rich model of residential mobility, in which individual households interact with other households and real-estate infrastructure, dynamically in space and time, to form synthetic communities and artificial property submarkets. Use of the model for what-if experimentation is demonstrated with synthetic economic and sociodemographic simulation scenarios.

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References

2007

Cellular Automata

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The checkerboard model of social interaction

Cited by 191 publications

References 2 publications

Tutorial on agent-based modelling and simulation

Tutorial on agent-based modelling and simulation

A Geographic Automata Model of Residential Mobility

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