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, ...

Maja Schlüter ¹², Claudia Pahl-Wostl ³, Mechanisms of Resilience in Common-pool Resource Management Systems, Ecology and Society, Vol. 12, No. 2 (Dec 2007) ...

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 ...

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 ...

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 ...

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 ...

In this review, we introduce the broad range of techniques available for cell-based computational modeling. The approaches can range from highly detailed models of just a few cells and their ...