How to conduct more systematic reviews of agent-based models and foster theory development: Taking stock and looking ahead

Agent-based models (ABMs) are increasingly utilized in ecology and related fields, yet concerns persist regarding the lack of consideration for lessons learned from previous models. This study explores the potential of systematically conducted ABM reviews to contribute to cumulative science and theory development by synthesizing individual ABM...

Agent decision-making: The Elephant in the Room - Enabling the justification of decision model fit in social-ecological models

Agent-based models are particularly suitable to reflect the dynamics of humans, nature, and their interactions, making them a crucial approach for understanding social-ecological systems. The formalisations of human decision-making are central to resulting model behaviours. Despite awareness of the complexity of human behaviour in social...

Machine-assisted agent-based modeling: Opening the black box

While agent-based modeling (ABM) has become one of the most powerful tools in quantitative social sciences, it remains difficult to explain their structure and performance. We propose to use artificial intelligence both to build the models from data, and to improve the way we communicate models to stakeholders. Although machine learning is...

How to keep it adequate: A protocol for ensuring validity in agent-based simulation

There has so far been no shared understanding of validity in agent-based simulation. We here conceptualise validation as systematically substantiating the premises on which conclusions from simulation analysis for a particular modelling context are built. Given such a systematic perspective, validity of agent-based models cannot be ensured if...