Agent-based models (ABMs) are powerful for handling such complexity in CHANS models, facilitating in-depth understanding of CHANS dynamics. ABMs have been employed mostly on a site-specific basis, ...

Agent-based modeling is a longstanding but underused method that allows researchers to simulate artificial worlds for hypothesis testing and theory building. Agent-based models (ABMs) offer ...

Environmental change can lead to human migration and vice versa. Agent-based models (ABMs) are valuable tools to study these linkages because they can represent individual migration decisions of human ...

The authors propose agent-based modeling for the study of decentralized finance and decentralized autonomous organizations.

What is agent-based modeling, otherwise known as ABM? What is distributed computing? Why do it? These are all easily answered questions, right? Surprisingly, the answer is a resounding “No!” in many ...

This course focuses on the exploration, construction and analysis of multi-agent models. Sample models from a variety of content domains are explored and analyzed. Spatial and network topologies are ...

One of the main challenges in Agent-Based Modeling (ABM) is to model agents’ preferences and behavioral rules such that the knowledge and decision-making processes of real-life stakeholders will be ...

A thorough analysis of risks in the banking system requires incorporating banks’ inherent heterogeneity and adaptive behavior in response to shocks and changes in business conditions and the ...