Abstract

Model of a human-machine system to express the process of cognition-intention-action is presented by referring a concept of an attention in Global Workspace Theory. Based on the model, new approach to estimate intentions of an operator who manipulates machines is proposed by utilizing Self-Organizing Map (SOM) and the Bayes filtering. Probabilities of transition of intentions are approximated by SOM from the operational log data, and the intentions are estimated through a Bayesian particle filtering with the trained SOM. The effectiveness was verified by applying to the remote operational task, and potential of the intention estimator was confirmed. Several issues were analyzed, and guideline for further improvement is discussed.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.