Yupana is a dynamic modeling and simulation project for better understanding complex systems. Complex systems have components that share large numbers of interrelations and interdependencies, making them difficult to understand with conventional tools.
Yupana’s structure is based on an adapted hierarchical Agent Based Model (ABM). Collections of agents form higher level units called agent group nodes and are based on the functional properties of the components within the system being modeled. Learn more about the Yupana Model
Agents and nodes are fed asynchronous data updates which alter their status, and subsequently the state of the network. To facilitate data collection, filtering, and processing, Yupana leverages an array of Natural Language Processing (NLP) and Machine Learning (ML) tools.
Within the Yupana model, agent based frameworks and machine learning will aggregate, organize, and relate data with real-time updates from our Spring Cloud Infastructure. Yupana simulations are integrated into Splunk for storing model outputs and producing analytics.