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This paper presents a real-time visualization solution for the multi-agent simulator WellProdSim, designed to analyze social well-being and productivity in rural Colombian communities. Originally, the WellProdSim social simulator was designed as a tool for academic researchers; now, it also features a user-friendly interface for administrative and policy makers users. The new system includes a Java-based simulation engine, implemented in the BESA multiagent framework, running as a standalone executable program without external dependencies, and a graphical interface built with ElectronJS and Next.js. A WebSocket channel enables synchronous transmission of key data, such as health and productivity parameters and emotional scales. It also records historical data in CSV format for detailed statistical analysis. This modular, scalable approach supports dynamic parameter configuration, interactive geographical referenced maps and the display of indicator charts, and sets the stage for integrating BDI-based emotional agents, enhancing the process of decision-making based on simulations of complex socioeconomic contexts.

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From Console to Dashboard: A Demonstration of Real-Time Visualization for Social Simulation with WellProdSim

  • 会议论文

  • 发表日期：

    2026年

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  • Jairo E. Serrano,
  • Adrian D. Vizcaino-Rio,
  • Mauricio A. Donado-Canedo,
  • Andrés F. García-Teheran,
  • Samuel L. Tobio Florez,
  • Enrique González

摘要

This paper presents a real-time visualization solution for the multi-agent simulator WellProdSim, designed to analyze social well-being and productivity in rural Colombian communities. Originally, the WellProdSim social simulator was designed as a tool for academic researchers; now, it also features a user-friendly interface for administrative and policy makers users. The new system includes a Java-based simulation engine, implemented in the BESA multiagent framework, running as a standalone executable program without external dependencies, and a graphical interface built with ElectronJS and Next.js. A WebSocket channel enables synchronous transmission of key data, such as health and productivity parameters and emotional scales. It also records historical data in CSV format for detailed statistical analysis. This modular, scalable approach supports dynamic parameter configuration, interactive geographical referenced maps and the display of indicator charts, and sets the stage for integrating BDI-based emotional agents, enhancing the process of decision-making based on simulations of complex socioeconomic contexts.