Ken A. Hawick
Schelling segregation, Agent-based model, Neighbourhood effects, Multiple species, Agent simulation
Multiple species effects in agent-based models can resolve stand-offs and obstacles to model systems that are evolving towards a long term static or dynamic equilibrium. The Schelling model of segregation is simulated using a range of different individual agent species. The agents are found to form complex spatial structures as they self-organise to maximise their segregation. We implement a custom simulation code to explore a large range of numbers of agent species. We describe various measures of complexity such as the bulk agent satisfaction fraction, the agent membership of the largest community, and the number of separate community clusters, that can all be used to locate the phase transition in the satisfaction parameter for various geometric configurations of the model. We report on systems of up to ten separate agent species on square, triangular and hexagonal lattices and also discuss implications of reversing the sense of the agent satisfaction to promote anti-ferromagnetic structures.
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