Validating Agent Based Social Systems Models
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Abstract
Validating social systems is not a trivial task. The paper outlines some of our past efforts in validating models of social systems with cognitively detailed agents. It also presents some of the challenges faced by us. A social system built primarily of cognitively detailed agents can provide multiple levels of correspondence, both at observable and abstract aggregated levels. Such a system can also pose several challenges including large feature spaces, issues in information elicitation with database, experts and news feeds, counterfactuals, fragmented theoretical base, and limited funding for validation. Our own approach to validity assessment is to consider the entire life cycle and assess the validity under four broad dimensions of methodological validity, internal validity, external validity and qualitative, causal and narrative validity. In the past, we have employed a triangulation of multiple validation techniques, including face validation as well as formal validation tests including correspondence testing.