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Agent-based models and mixed crop-ruminant livestock systems: advances; gaps; and implications for decision-making
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DOI：10.3389/fsufs.2026.1674409.png)
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Abstract
En 中文
Agent-based (AB) models have emerged as powerful tools for the simulation of agricultural systems; enabling researchers and policymakers to explore complex interactions among biophysical processes; human decision-making; and socio-ecological dynamics. In mixed crop-livestock systems; AB models hold particular promise for evaluating alternative management strategies; improving resource use; and assessing trade-offs between economic performance and environmental outcomes. However; the application of AB models to these mixed systems remains limited; with significant gaps in representing behavioural diversity; feedback mechanisms; and structural complexity. This review synthesizes the current state of AB model applications in agriculture and identifies key gaps in their development and use for mixed crop-livestock systems. Using the Rural Futures Multi-Agent Simulation (RF-MAS) model as a case study; we highlight the strengths and limitations of current modelling approaches. We argue that future agent-based models must incorporate more realistic agent behaviours; system-level interactions; and context-specific constraints to better support decision-making in these integrated systems.
Keywords:
livestock
farmers
crops
human behaviour
socio-ecological dynamics
agent decision-making
biophysical processes
mixed agricultural systems
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