Interpreting trainee intent in real time in a simulation-based training system

Transactions of the Society for Computer Simulation

Volumn 17, Issue 3, 2000, Pages 135-147

  Gonzalez, Avelino J ^a   Drewes, Peter J ^a   Gerber, William ^a  

^a UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

After action review; Automated performance monitoring simulation and training; Case based reasoning; Flight training; Human behavior representation; Template based interpretation; Training

Indexed keywords

EID: 33747391644     PISSN: 07406797     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (22)

1. McGraw, K. Performance Support Systems: Integrating AI, Hypermedia, and CBT to Enhance User Performance. Journal of Artificial Intelligence in Education, Vol. 31, No. 3, pp 88-93, 1994.
2. Charles, J. Design Guidelines for Trainer Instructor/Operator Stations. NAWC-TSD Technical Report, Naval Training Systems Center, 1994.
3. Thurman, R. Applying Artificial Intelligence to Training Air Combat Maneuvering: The Potential, The Pitfalls, The Products. Air Force Armstrong Laboratory Technical Report, 1992.
4. Moreno, M. Introduction to Artificial Intelligence in Training Systems. Proceedings of the IEEE Summer Conference on AI, pp 122-128, 1984.
5. DeJong, T. Learning and Instruction with Computer Simulations. Education and Computing, Vol. 6, pp 23-41, 1991.
6. Williams, K. and Reynolds, R. The Integration of Surface Warfare Simulation with Instructional Training Technology. Naval Training Systems Center, Technical Report, 1998.
7. Kulikowski, K.A. and Weiss, S.M. Representation of Expert Knowledge for Consultant. Artificial Intelligence for Medicine, Peter Szolovits (Ed.), Westview Press, Boulder, CO, 1982.
8. Kurland, L., Granville, R. and MacLaughlin, D. Design, Development and Implementation of an Intelligent Tutoring System for Training Radar Mechanics to Troubleshoot. Intelligent Instruction by Computer, Vol. 16, pp 340-351, 1992.
9. Newman, D., Grignetti, M., Gross, M. and Massey, D. Intelligent Conduct of Fire Trainer: Intelligent Technology Applied to Simulator-Based Training. Intelligent Instruction by Computer, Springer-Verlag, 1991.
10. Takeuchi, A. and Otsuki, S. A Study of Student Models and Learner-Machine Interaction. Artificial Intelligence Tools in Education, Vol. 4, pp 199-204, 1987.
11. Bushman, J. and Mitchell, C. ALLY: An Operator's Associate for Cooperative Supervisory Control Systems. IEEE Transactions on Systems, Man and Cybernetics, Vol. 23, No. 1, pp 750-763, January 1993.
12. Wang, D. and Avbib, M. Timing and Chunking in Processing Temporal Order. IEEE Transactions on Systems, Man, and Cybernetics, Vol. 23, No. 4, pp 993-1009, 1993.
13. Maskara, A. and Noetzel, A. Training Auto-associative Recurrent Neural Network with Preprocessed Training Data. Proceedings of the SPIE-The International Society for Optical Engineering: Science of Artificial Neural Networks II, pp 420-428, Orlando, FL, April 13-16, 1993.
14. Liu, A. and Pentland, A. Towards Real-time Recognition of Driver Intentions. Proceedings of the 1997 IEEE Conference on Intelligent Transportation Systems, pp 236-241, Boston, November 1997.
15. Narendra, K.S., Balakrishnan, J., and Ciliz, M.K. Adaptation and Learning using Multiple Models, Switching, and Tuning, IEEE Control Systems Magazine, Vol. 15, No. 3, pp 37-51, 1995.
16. th Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Magnificent Milestones and Emerging Opportunities in Medical Engineering, October 30-November 2, 1997, pp 1458-1461, Chicago, 1997.
17. Weng, J.J. and Hwang, W. Toward Automation of Learning: The State Self-organization Problem for a Face Recognizer. Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition, Nara, Japan, April 14-16, 1998, pp 384-389.
18. Schroeder, S.C. and Vaughn, L.E. Fast Intent Recognition System. AGARD Conference Proceedings No. 149 on Real Time Computer Based Systems, 1974.
19. Strohal, M. and Onken, R. Intent and Error Recognition as part of a Knowledge-based Cockpit Assistant. Proceedings of the SPIE Conference, April 1998.
20. th International Conference on User Modeling-UM99, 1999.
21. Drewes, P.J. Automated Student Performance Monitoring in Training Simulations. Doctoral Dissertation, ECE Department, University of Central Florida, 1997.
22. Gonzalez, A.J. and Ahlers, R. Context-based Representation of Intelligent Behavior in Training Simulations. TRANSACTIONS of the Society for Computer Simulation, Vol. 15, No. 4, pp 153-166, 1998.