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Agent-Based Models

In this step we would like to say something more about the type of models typically used for basic simulations. These models tend to be quite simple examples of a wider group called agent-based models, or ABMs for short.
Agent Based Models
© ACTISS
In this step we would like to say something more about the type of models typically used for basic simulations. These models tend to be quite simple examples of a wider group called agent-based models, or ABMs for short.

Those models are based on individuals, called agents. Who are those agents? In previous steps, our simulations agents were inhabitants of all Fruit County villages we were experimenting with. However, in a wider sense those agents might be both individuals and people, animals, or collective entities, such as organizations or groups. They interact with each other, they decide what to do on the basis of what is happening with other agents (for example neighbours in our simulation, or friends in the Grapevine example) and may have different strategies.

Bear in mind that there are a set of rules that lead the agents’ behaviour. In case of spatial models the agents are spatially distributed in some specific and defined environment. In our case this environment looked a bit like a big chessboard, but this is just one example and it might look different.

Uthree rows and columns of schematic houses all looking the same except the middle house (2nd row, 2nd column)

Uses of Agent-Based Models

Agent-based models can be useful for analysing and illustrating various phenomena. They can be used for simulation of biological processes, interactions between animals, urban planning, epidemiology, consumer behaviour, crowd behaviour, social influence (how we influence other people with our opinions), migration processes and many, many others.

ABMs and Social Scientists

For social scientists this approach is especially fruitful due to the fact that we’re focusing on the agents and their behaviour, which is a really natural way of thinking for social scientists. Then, by setting the rules, environment and relations between the agents we can study and better understand social processes. In addition, we can visualise it all in such a way that some insights are plainly visible.

With all that in mind, please watch a short interview with Joshua Epstein, one of the most prominent specialists in the field of social simulation (and author of Generative Social Science: Studies in Agent-Based Computational Modeling), speak about different applications of agent-based models.

This is an additional video, hosted on YouTube.

One note: this interview was made before the pandemic started, so the beginning of the interview may sound a bit disturbing.

Additional watching:

For those of you who want to know a bit more about agent-based models we recommend watching this video (you can also use it as a podcast).

This is an additional video, hosted on YouTube.

© ACTISS
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People, Networks and Neighbours: Understanding Social Dynamics

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