Agent-Based Modelling

Dear Colleagues,

In the last 30 years, agent-based modeling (ABM) and related similar approaches with different nuances and names (e.g., agent-based systems (ABSs), individual-based modeling (IBM), multi-agent systems (MASs), or multi-agent-based simulations (MABSs)) have shifted from being a heterodox modeling approach to become a recognized research methodology, in many cases one of the mainstream modeling techniques, in a wide range of scientific disciplines.

In an agent-based model, the individuals or entities that participate in a system under study and the interactions between them and with the environment are explicitly modeled as computational agents and interactions. This modeling approach presents important advantages, since it facilitates the abstraction of complex systems, the integration of spatial elements, including heterogeneity in the representation, and enables the use of computers as an inference engine. However, it also entails some problems such as the use of induction for the generalization of results, the verification and validation of the models, or the reuse of code and scalability.

This Special Issue not only aims to advance the methodological elements of the modeling process using agent technologies, but also to showcase rigorous uses of theoretical and empirical ABM in different applied domains and disciplines.

Prof. Dr. José Manuel Galán
Dr. José Ignacio Santos
Dr. Ruben Fuentes-Fernández
Guest Editors

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