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Agent Based Models

By: Edmund Chattoe-Brown | Edited by: Paul Atkinson, Sara Delamont, Alexandru Cernat, Joseph W. Sakshaug & Richard A. Williams Published: 2019 | Length:   10 | DOI: |
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An agent based model (ABM) is the product of a research method that represents social processes as a particular type of computer programme using special software. This distinguishes it from representations in well-known social science research methods like equations (found in regression models) or narratives (found in ethnographic analysis). The entry begins by illustrating the method using an example of innovation diffusion, justifies its distinctive methodology and distinguishes it from existing quantitative and qualitative methodologies, discusses the different uses to which an ABM can be put (and how one justifies the claim that these uses have been effective scientifically), presents the challenges and opportunities of interfacing agent based modelling with existing (and novel) social science data, demonstrates the hazards of unsystematic agent based modelling research relative to existing approaches, shows what is necessary for agent based modelling to become a progressive research method (producing models of steadily improving quality over time), looks at a range of practical challenges researchers may face in applying agent based modelling, relates the unique contribution of agent based modelling and its methodology to its potential role in prediction and effective policy, and presents conclusions about how agent based modelling can develop and improve itself in the future. The aim of the entry is to offer the reader an overview of some of the major issues in the field and provide a starting point for them to build or evaluate ABMs relevant to their own research interests.

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Agent-based simulation

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