FURI | Fall 2018

Classification of Multi-Agent Interaction in Biological Systems Using Machine Learning

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Interactions among biological agents are of scientific value. These interactions may be used by agents to form strategies, cooperate with one another, or establish a hierarchy. The ability to classify and predict these interactions enables researches to derive models from them. These models can then be applied to a broader context, such as cyber-security, to better understand malicious and cooperative behavior among botnets. The purposes of interactions vary, the classification process does not. The researchers have proposed a general methodology for classifying video footage of interactions within biological colonies. The process is a step toward prediction of live systems.

Student researcher

Portrait of Ricardo Weir

Ricardo Weir

Computer science

Hometown: Phoenix, Arizona

Graduation date: Fall 2018

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