A Connectionist Modeling Approach to Rapid Analysis of Emergent Social Cognition Properties in Large-Populations

Abstract

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.

Publication
Human Behavior-Computational Modeling and Interoperability Conference

[Pub 2]

Kalyan Perumalla
Kalyan Perumalla

Kalyan Perumalla is Founder and President of Discrete Computing, Inc. He led advanced research and development at ORNL and holds senior faculty appointments at UTK, GT, and UNL.

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