
Worked on the ADimoska/SOMASExtended repository to enhance agent-based modeling by refining agent contribution and rank-based decision logic. Focused on backend development in Go, the work involved refactoring agent behavior naming, introducing rank thresholds, and implementing algorithms to calculate the amount needed for agents to reach the next rank. Stability improvements addressed segmentation faults and corrected agent type initialization, while graph visualization was enhanced for better data visibility. By averaging recent contributions and refining withdrawal calculations, the updates enabled more accurate, rank-informed decisions and improved reliability of simulation outcomes, supporting data-driven planning and reducing operational risk within the system.
December 2024 monthly summary for ADimoska/SOMASExtended: Focused on delivering robust agent behavior improvements, stabilizing runtime, and enhancing data visibility. Business value was enabled through more accurate contribution metrics, reliable decision logic, and improved graph-based insights.
December 2024 monthly summary for ADimoska/SOMASExtended: Focused on delivering robust agent behavior improvements, stabilizing runtime, and enhancing data visibility. Business value was enabled through more accurate contribution metrics, reliable decision logic, and improved graph-based insights.

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