Keywords
cropping plan, dynamic decision-making, model, bdi, uml
Start Date
1-7-2010 12:00 AM
Abstract
Every year farmers have to allocate their fields to different crops and crop management. These choices depend on multiple spatial and temporal factors, farmers’ strategy and risk behaviour. To support farmers in these complex decisions and efficiently allocate scarce resources, we studied cropping plan decisions in arable farms with the aim of simulating contextual changes. A deeper understanding of these processes at farm level is then a start to model and design flexible and environmental-friendly cropping systems. We propose a stepwise approach to study and formalize the complexity of the decision-making processes based on farmer’s interviews and on modelling approach inspired from software development methods. We made use of semi-structured farmer’s interviews (n=30) to define farm constraints in relation to farmers strategies that affect cropping plan decisions. We identified objects/concepts that farmers use to decide their cropping plan and gathered them into an ontology. We sketched out individual decision model using abductive reasoning to capture the dynamic of the decision-makings. All individual decision models were used as so many hypothesis to build a more generic cropping plan decision models through an inductive and iterative integration. We took into consideration that farmers decisions involve anticipation, uncertainty and risk.
Modelling the Complexity of the Cropping Plan Decision-making
Every year farmers have to allocate their fields to different crops and crop management. These choices depend on multiple spatial and temporal factors, farmers’ strategy and risk behaviour. To support farmers in these complex decisions and efficiently allocate scarce resources, we studied cropping plan decisions in arable farms with the aim of simulating contextual changes. A deeper understanding of these processes at farm level is then a start to model and design flexible and environmental-friendly cropping systems. We propose a stepwise approach to study and formalize the complexity of the decision-making processes based on farmer’s interviews and on modelling approach inspired from software development methods. We made use of semi-structured farmer’s interviews (n=30) to define farm constraints in relation to farmers strategies that affect cropping plan decisions. We identified objects/concepts that farmers use to decide their cropping plan and gathered them into an ontology. We sketched out individual decision model using abductive reasoning to capture the dynamic of the decision-makings. All individual decision models were used as so many hypothesis to build a more generic cropping plan decision models through an inductive and iterative integration. We took into consideration that farmers decisions involve anticipation, uncertainty and risk.
