Companion Modelling and Multi-Agent Systems
Co-designing an agent-based model to represent rainfed lowland rice management in lower northeast Thailand
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In northeast Thailand, rice production is constrained by erratic rainfall and coarse textured soils leading to low yields, and low per capita incomes. Labour migration is a common adaptive strategy of resource- poor farmers. A better understanding of the interaction between labour migration and land and water use is needed as the authorities plan massive investments in new irrigation infrastructure. This research used the Companion Modelling (ComMod) approach to facilitate co-learning about this key interaction between researchers and a heterogeneous group of local rice farmers. This long ComM...
In northeast Thailand, rice production is constrained by erratic rainfall and coarse textured soils leading to low yields, and low per capita incomes. Labour migration is a common adaptive strategy of resource- poor farmers. A better understanding of the interaction between labour migration and land and water use is needed as the authorities plan massive investments in new irrigation infrastructure. This research used the Companion Modelling (ComMod) approach to facilitate co-learning about this key interaction between researchers and a heterogeneous group of local rice farmers. This long ComMod process, associating modelling tools such as Role-Playing Games (RPG) and successive versions of an Agent-Based Model (ABM), was implemented with rice farmers. A shared representation of the interaction under study was achieved to be used for joint exploration of possible future scenarios. Farmers consider that the co-designed ABM, sufficiently represents their farm management and labour migration practices. They also found that such a process, stimulated by evolutionary gaming and simulation exercises, is effective to facilitate knowledge exchange and integration.
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