Hidden order: how adaptation builds complexity
Hidden order: how adaptation builds complexity
Cormas: Common-Pool Resources and Multi-agent Systems
IEA/AIE '98 Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial In telligence and Expert Systems: Tasks and Methods in Applied Artificial Intelligence
Further towards a taxonomy of agent-based simulation models in environmental management
Mathematics and Computers in Simulation - Selected papers of the MSSANZ/IMACS 14th biennial conference on modelling and simulation
Mediated Modeling: A System Dynamics Approach to Environmental Consensus Building
Mediated Modeling: A System Dynamics Approach to Environmental Consensus Building
Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity)
Interaction-Oriented Agent Simulations: From Theory to Implementation
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Entity-relationship and object-oriented formalisms for modeling spatial environmental data
Environmental Modelling & Software
Assessing the likelihood of realizing idealized goals: The case of urban water strategies
Environmental Modelling & Software
Spatial agent-based models for socio-ecological systems: Challenges and prospects
Environmental Modelling & Software
Behaviour and space in agent-based modelling: Poverty patterns in East Kalimantan, Indonesia
Environmental Modelling & Software
Review: A critical review of integrated urban water modelling - Urban drainage and beyond
Environmental Modelling & Software
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Viewing an urban water system as a complex adaptive system provides new opportunities for analysis and avoids some critical simplifications. Taking this perspective, it is possible to explore the inter-related effects of changes to the system. This is particularly important in the developing world where donors providing aid aim to improve conditions but struggle to understand and quantify the systemic impacts of their actions. This is because an intervention aiming to improve condition may also have unintended and undesirable effects. To provide decision support, this paper describes an agent-based model of an urban water system, developed on the basis of ethnographic interviews, and subsequently evaluated by local stakeholders. The paper describes the model design as well as the results of scenarios. The model provides guidance on which system amendments may produce the best outcomes in terms of output variables, and on the basis of sense-checking and sensitivity analysis it is judged that model results are likely to give a good indication about possible real world outcomes. It is clear that no single strategy will solve all problems on its own, but that a combined strategy - with a strong focus on groundwater management and protection - is likely to be most successful.