Comparing Learning Techniques for Hidden Markov Models of Human Supervisory Control Behavior

Comparing Learning Techniques for Hidden Markov Models of Human Supervisory Control Behavior

Models of human behaviors have been built using many different frameworks. In this paper, we make use of Hidden Markov Models (HMMs) applied to human supervisory control behaviors. More specifically, we model the behavior of an operator of multiple heterogeneous unmanned vehicle systems. The HMM fra...

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Bibliographic Details
Main Authors: Cummings, M. L. (Contributor), Las Fargeas, Jonathan C. (Contributor), Roy, Nicholas (Contributor), Boussemart, Yves (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Humans and Automation Lab (Contributor), Massachusetts Institute of Technology. School of Engineering (Contributor)
Format: Article
Language:English
Published: American Institute of Aeronautics and Astronautics, 2010-07-14T16:04:21Z.
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