Traditional modeling methodologies, such as those based on rule-based agent modeling, are exhibiting limitations in application to rich behavioral scenarios, especially when applied to large population aggregates. Here, we propose a new modeling methodology based on a well-known ‘connectionist approach,’ and articulate its pertinence in new applications of interest. This methodology is designed to address challenges such as speed of model development, model customization, model reuse across disparate geographic/cultural regions, and rapid and incremental updates to models over time.
[Pub 2]