Geretation of Multiagent Simulation Models Based on Machine Learning from Political and Economical Data

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Several techniques to generate multiagent simulation models based on machine learning from political and economical data. This work includes implementation of a system that generates simulation models using machine learning technique, collects data using crowd-sourcing services, and supports to combine such models and to construct large and complex simulation models. Basic technologies has been established, such as machine learning from social data, metadata to annotate simulation models, and model analysis using program dependency graphs (PDGs).