Would-be worlds: how simulation is changing the frontiers of science
Would-be worlds: how simulation is changing the frontiers of science
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
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
Land market mechanisms for preservation of space for coastal ecosystems: An agent-based analysis
Environmental Modelling & Software
Environmental Modelling & Software
Position Paper: The role of expert opinion in environmental modelling
Environmental Modelling & Software
A multi-agent model system for land-use change simulation
Environmental Modelling & Software
Environmental Modelling & Software
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Rainfed lowland rice production in lower Northeast Thailand is a complex and adaptive farming activity. Complexity arises from interconnections between multiple and intertwined processes, affected by harsh climatic and soil conditions, cropping practices and labor migrations. Having faced a spatially heterogeneous and dynamic environment for centuries, local rice farmers are very adaptive and are used to adjusting their behavior in unpredictable climatic and economic conditions. Better understanding is needed to manage the key interactions between labor, land and water use for rice production, especially when major investments in new water infrastructure are now being considered. Based on the principles of the iterative and evolving Companion Modeling (ComMod) approach, indigenous and academic knowledge was integrated in an Agent-Based Model (ABM) co-designed with farmers engaged in different types of farming practices over a period of three years to create a shared representation of the complex and adaptive social-agroecological system in Ban Mak Mai village, in the south of Ubon Ratchathani province. The ABM consists of three interacting modules: Water (hydro-climatic processes), Rice, and Household. ''Household'' is a rule-based agent; it makes daily decisions based on its available means of production, taking into account the stage of the rice crop, and water and labor availability. Key decisions made are related to: i) rice nursery establishment, ii) rice transplanting, iii) rice harvesting, and iv) migration of household members. The spatially explicit model interface represents a virtual rainfed lowland rice environment as an archetypical toposequence made of upper to lower paddies in a mini-catchment farmed by 4 different households, and also includes water bodies and human settlements. Thanks to intensive communication, the participating farmers, made sure that the ABM adequately represents their rice farming and labor migration management practices. They found the model useful to deepen their understanding of the interrelations between labor migrations and rice production, which helped to strengthen their adaptive management ability.