Using 4D/RCS to address AI knowledge integration

AI Magazine

Volumn 27, Issue 2, 2006, Pages 71-81

  Schlenoff, Craig ^a   Albus, Jim ^a   Messina, Elena ^a   Barbera, Anthony J ^b   Madhavan, Raj ^a   Balakirsky, Stephen ^a  

^a NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY   (United States)

^b NIST ^*

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; KNOWLEDGE REPRESENTATION; OPTICAL RADAR; REMOTELY OPERATED VEHICLES;

AUTONOMOUS NAVIGATION; ICONIC KNOWLEDGE; SYMBOLIC KNOWLEDGE;

KNOWLEDGE BASED SYSTEMS;

EID: 33745896193     PISSN: 07384602     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (24)

1. Albus, J. 1971. A Theory of Cerebellar Function. Mathematical Biosciences 10(1-2): 25-61.
2. Albus, J. 1997. The NIST Real-time Control System (RCS): An Approach to Intelligent Systems Research. Journal of Experimental and Theoretical Artificial Intelligence 9: 157-174.
3. Albus, J. S. 1981. Brain, Behavior, and Robotics. New York: McGraw-Hill.
4. Albus, J. S.; Balakirsky, S. B.; Bostelman, R. V.; Bunch, R.; Chang, T.; Dagalakis, N. G.; Falco, J. A.; Finkelstein, R.; Gilsinn, J. D.; Hong, T. H.; Huang, H.-M.; Jacoff, A. S.; Juberts, M.; Kramer, T. R.; Lacaze, A. D.; Legowik, S. A.; Messina, E. R.; Michaloski, J. L.; Murphy, K. N.; Norcross, R. J.; Proctor, F. M.; Rippey, W. G.; Scott, H. A.; Shackleford, W. P.; Shneier, M. O.; Stouffer, K. A.; Szabo, S.; Wavering, A. J. 2002. 4D/RCS Version 2.0: A Reference Model Architecture for Unmanned Vehicle Systems. NISTIR 6910. Gaithersburg, MD: National Institute of Standards and Technology, Office of Information Services.
5. Albus, J. S.; and Meystel, A. 2001. Engineering of Mind. New York: John Wiley & Sons.
6. Anderson, J. 1983. The Architecture of Cognition. Mahwah, N.J.: Lawrence Erlbaum Associates.
7. Archer, R.; Lebriere, C.; Warwick, W.; and Schunk, D. 2003. Integration of Task Network and Cognition Models to Support System Design. Paper presented at the Collaborative Technology Alliances Conference, April 29-May 1, College Park, MD.
8. Archer, S.; and Adkins, R. 1999. IMPRINT User's Guide. Washington, D.C.: U.S. Army Research Laboratory, Human Research and Engineering Directorate.
9. Balakirsky, S. 2003. A Framework for Planning with Incrementally Created Graphs in Attributed Problem Spaces. Berlin: IOS Press.
10. Barbera, T.; Albus, J.; and Fitzgerald, M. 1979. Hierarchical Control of Robots Using Microcomputers. In Proceedings of the 9th International Symposium on Industrial Robots. Dearborn, MI: Society of Manufacturing Engineers.
11. Barbera, T.; Fitzgerald, M.; Albus, J.; and Haynes, L. S. 1984. RCS: The NBS Real-Time Control System. Paper presented at the Robots Conference and Exposition, June 4-7, Detroit, Michigan.
12. Camden, R.; Bodt, B.; Schipani, S.; Bornstein, J.; Phelps, R.; Runyon, T.; French, F.; and Shoemaker, C. 2003. Autonomous Mobility Technology Assessment Interim Report, Army Research Laboratory (ARL-MR-565). Washington, DC: Government Printing Office.
13. Dickmanns, E. D. 1999 An Expectation-Based Multi-Focal Saccadic (EMS) Vision System for Vehicle Guidance. In Proceedings of the 9th International Symposium on Robotics Research (ISRR'99). Stanford, CA: International Foundation of Robotics Research.
14. Gonzalez, C. 2003. ACT-R Implementation of an Instance-Based Decision Making Theory. Paper presented at the Collaborative Technology Alliance Conference. April 29-May 1, College Park, MD.
15. Kieras, D.; and Meyer, D. E. 1997. An Overview of the Epic Architecture for Cognition and Performance with Application to Human-Computer Interaction. Human-Computer Interaction 12(4): 391-438.
16. Laird, J. E.; Newell, A.; and Rosenbloom, P. S. 1987. SOAR: An Architecture for General Intelligence. Artificial Intelligence 33(1): 1-64.
17. Madhavan, R.; Hong, T.; and Messina, E. 2004. Temporal Range Registration for Unmanned Ground and Aerial Vehicles. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 3180-3187. Piscataway, NJ: Institute for Electrical and Electronics Engineers.
18. Madhavan, R.; and Messina, E. 2003. Iterative Registration of 3D LADAR Data for Autonomous Navigation. In Proceedings of the IEEE Intelligent Vehicles Symposium, 186-191. Piscataway, NJ: Institute for Electrical and Electronics Engineers.
19. Minton, S. N. 1990. Quantitative Results Concerning the Utility of Explanation-Based Learning. Artificial Intelligence 42(2-3): 363-391.
20. Provine, R.; Uschold, M.; Smith, S.; Balakirsky, S.; and Schlenoff, C. 2004. Observations on the Use of Ontologies for Autonomous Vehicle Navigation Planning. In Knowledge Representation and Ontologies for Autonomous Systems: Papers from the 2004 AAAI Spring Symposium, 98-103. AAAI Technical Report SS-04-04, Menlo Park, CA, American Association for Artificial Intelligence. Revised and expanded edition to appear in the Robotics and Autonomous Systems Journal.
21. Schlenoff, C.; Balakirsky, S.; Barbera, T.; Scrapper, C.; Ajot, J.; Hui, E.; and Paredes, M. 2004. The NIST Road Network Database: Version 1.0, National Institute of Standards and Technology (NIST) Internal Report 7136, Gaithersburg, MD.
22. Schlenoff, C.; Washington, R.; and Barbera, T. 2004. Experiences in Developing an Intelligent Ground Vehicle (IGV) Ontology in Protégé. Paper presented at the 7th International Protégé Conference, Bethesda, MD, July 6-9.
23. Shapiro, D.; and Langley, P. 1999. Controlling Physical Agents through Reactive Logic Programming. In Proceedings of the Third International Conference on Autonomous Agents, 386-387. New York: ACM Press.
24. Witzgall, C.; Check, G.; and Gilsinn, D. 2003. Terrain Characterization from Ground-Based LADAR. Paper presented at the PerMIS 2003 Workshop, National Institute of Standards and Technology, September, Gaithersburg, MD.