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Task Engagement Inference Within Distributed Multiparty Human-Machine Teaming via Topic Modeling

  • Nia PetersEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 962)

Abstract

Research in Intelligent Awareness Systems (IAS) focuses on designing systems that are aware of their current environment by monitoring human interactions and making inferences on when to engage with human counterparts. A potential gap is task engagement inference for distributed human-machine teaming. The objective of this paper is a proposed intelligent awareness system via task topic modeling for task engagement inference within these domains. If the system has information on “what” teammates are discussing or the task topic, it is better informed prior to engaging. The proposed task topic model is applied to two simulated multiparty, distributed teaming interactions and evaluated on its ability to infer the current task topic. For both tasks, the model performs well over the random baseline, however the performance is degraded for interactions with more robust dialogue. This work has the potential of informing the development of intelligent awareness systems within distributed multiparty teaming and collaborative endeavors.

Keywords

Task engagement inference Human-systems integration Human-machine teaming Topic modeling 

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Copyright information

© This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2020

Authors and Affiliations

  1. 1.Battlespace Acoustic Branch, 711th Human Performance Wing, Air Force Research LaboratoryDaytonUSA

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