Agent-based modelling for knowledge synthesis and decision support

Community member post by Jen Badham

Jen Badham (biography)

The most familiar models are predictive, such as those used to forecast the weather or plan the economy. However, models have many different uses and different modelling techniques are more or less suitable for specific purposes.

Here I present an example of how a game and a computerised agent-based model have been used for knowledge synthesis and decision support.

The game and model were developed by a team from the Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), a French agricultural research organisation with an international development focus. The issue of interest was land use conflict between crop and cattle farming in the Gnith community in Senegal (D’Aquino et al. 2003).

Agent-based modelling is particularly effective where understanding is more important than prediction. This is because agent-based models can represent the real world in a very natural way, making them more accessible than some other types of models. Continue reading

Learning to tackle wicked problems through games / Aprendiendo a hacer frente a problemas perversos a través de los juegos/ Apprendre à affronter les problèmes sournois à travers les jeux

Community member post by Claude Garcia, Anne Dray and Patrick Waeber

claude-garcia
Claude Garcia (biography)

A Spanish version and a French version of this post are available

Can we help the next generation of policy makers, business leaders and citizens to become creative, critical and independent thinkers? Can we make them aware of the nature of the problems they will be confronted with? Can we strengthen their capacity to foster and lead stakeholder processes to address these problems?

Yes. Continue reading