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dc.creatorLe, Quang Baoen_US
dc.date.accessioned2016-04-28T14:16:49Z
dc.date.available2016-04-28T14:16:49Z
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/KRvmswzeen_US
dc.identifier.citationQuang Bao Le. (15/10/2015). Methodological options for modelling agent’s decision-making in multi-agent system model of coupled community-landscape systems.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/4708
dc.description.abstractThis visual-aided manual presents the state-of-the art methodological options for modeling human decision-making in general and in multi-agent system. The options include heuristic, rational, bounded rational and hybrid approaches. Assumptions, rationales and pseudo algorithms for each approach are briefly described. Depending on research goal, team capacity, preference and data availability researchers select one of the approaches to apply. However, it is important that they must understand the assumptions and rationales of the selected approach to realize the methodological limits. In general, the model of real-world decision-making of smallholder farmers favors the hybrid approach.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.rightsCC-BY-4.0en_US
dc.subjectagent-based systemsen_US
dc.subjectbehavioral changesen_US
dc.subjectdecisionen_US
dc.subjectmulti-agent systems (mas)en_US
dc.subjectadoptionen_US
dc.titleMethodological options for modelling agent’s decision-making in multi-agent system model of coupled community-landscape systemsen_US
dc.typePresentationen_US
dcterms.available2015-10-15en_US
cg.creator.idLe, Quang Bao: 0000-0001-8514-1088en_US
cg.subject.agrovocland managementen_US
cg.subject.agrovocland useen_US
cg.subject.agrovocsmallholder farmersen_US
cg.contributor.centerCGIAR Research Program on Dryland Systems - DSen_US
cg.contributor.crpCGIAR Research Program on Dryland Systems - DSen_US
cg.contributor.funderNot Applicableen_US
cg.coverage.regionGlobalen_US
cg.coverage.start-date2015-07-01en_US
cg.coverage.end-date2015-10-15en_US
dc.identifier.statusOpen accessen_US


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