Agent-based land-use models (ABLUMs) are increasingly used in land-use modelling to simulate human decision-making and its impact on land use. These models incorporate social interactions, adaptation, and decision-making at different levels, allowing for a mechanistic and spatially explicit representation of land-use dynamics. ABLUMs have been applied in various areas, including policy analysis, participatory modelling, explaining spatial patterns of land use, testing social science concepts, and understanding land-use functions. While they are primarily used by the research community to organize knowledge and explore theoretical aspects, there is a need to demonstrate their effectiveness in real-world problem-solving. ABLUMs are more useful as research tools to develop an underlying knowledge base that can be combined with end-user input into simple rules-of-thumb rather than as operational decision-support tools. ABLUMs have been used to analyze the impact of agricultural policies, such as the EU Agenda 2000, on land use and agricultural productivity. They have also been used to explore the effects of different policies on land use and environmental outcomes, such as the impact of phosphorus taxation on lake eutrophication. In participatory modelling, ABLUMs have been used in role-playing games to involve stakeholders in the development and testing of land-use models, allowing for a better understanding of complex social and environmental interactions. These models have also been used to explore the dynamics of land-use changes in different regions, such as the spread of urban areas in Thailand and the impact of deforestation in Indiana. ABLUMs have also been used to study the effects of social and economic factors on land use, such as the influence of social norms and institutions on agricultural practices. They have been used to model the interactions between farmers and loggers in the Philippines and to explore the dynamics of land use in different regions. The ability of ABLUMs to incorporate social processes and non-monetary influences on decision-making has made them valuable tools for understanding complex land-use systems. However, there is a need to ensure that these models are relevant to real-world problems and that knowledge is effectively shared between modellers and potential beneficiaries. While ABLUMs have shown promise in understanding complex land-use systems, they are not yet capable of predicting the behavior of specific households or communities with precision. Nevertheless, they remain a valuable tool for exploring the processes involved in interactions between the biophysical and socio-economic components of land-use systems.Agent-based land-use models (ABLUMs) are increasingly used in land-use modelling to simulate human decision-making and its impact on land use. These models incorporate social interactions, adaptation, and decision-making at different levels, allowing for a mechanistic and spatially explicit representation of land-use dynamics. ABLUMs have been applied in various areas, including policy analysis, participatory modelling, explaining spatial patterns of land use, testing social science concepts, and understanding land-use functions. While they are primarily used by the research community to organize knowledge and explore theoretical aspects, there is a need to demonstrate their effectiveness in real-world problem-solving. ABLUMs are more useful as research tools to develop an underlying knowledge base that can be combined with end-user input into simple rules-of-thumb rather than as operational decision-support tools. ABLUMs have been used to analyze the impact of agricultural policies, such as the EU Agenda 2000, on land use and agricultural productivity. They have also been used to explore the effects of different policies on land use and environmental outcomes, such as the impact of phosphorus taxation on lake eutrophication. In participatory modelling, ABLUMs have been used in role-playing games to involve stakeholders in the development and testing of land-use models, allowing for a better understanding of complex social and environmental interactions. These models have also been used to explore the dynamics of land-use changes in different regions, such as the spread of urban areas in Thailand and the impact of deforestation in Indiana. ABLUMs have also been used to study the effects of social and economic factors on land use, such as the influence of social norms and institutions on agricultural practices. They have been used to model the interactions between farmers and loggers in the Philippines and to explore the dynamics of land use in different regions. The ability of ABLUMs to incorporate social processes and non-monetary influences on decision-making has made them valuable tools for understanding complex land-use systems. However, there is a need to ensure that these models are relevant to real-world problems and that knowledge is effectively shared between modellers and potential beneficiaries. While ABLUMs have shown promise in understanding complex land-use systems, they are not yet capable of predicting the behavior of specific households or communities with precision. Nevertheless, they remain a valuable tool for exploring the processes involved in interactions between the biophysical and socio-economic components of land-use systems.