Dana S. Nau is a Professor of Computer Science and Systems Research at the University of Maryland Department of Computer Science in College Park, where he has done research in automated planning and scheduling, game theory, cognitive science, and computer-aided engineering. He has many PHD students, including Qiang Yang who graduated in 1989. He has more than 300 publications[1] and several best-paper awards.[citation needed] Some of his accomplishments include the discovery of game tree pathology,[2] the development of the SHOP and SHOP2[3] HTN planning systems, and the book Automated Planning: Theory and Practice (ISBN 1-55860-856-7).[4] He is a Fellow[5] of the AAAI and in 2022 he was elected as a Fellow of the AAAS.[6]
Dana S. Nau | |
---|---|
Born | December 1951 Illinois | (age 72)
Nationality | American |
Alma mater | Duke University - Ph.D., 1979 University of Missouri-Rolla - B.S., 1974 |
Known for | automated planning and scheduling, HTN planning, game tree pathology |
Scientific career | |
Fields | Computer Science, Artificial Intelligence, automated planning and scheduling, game theory |
Institutions | University of Maryland, College Park |
Honors
edit- 1996 – Fellow, AAAI
- 2013 – Fellow of the Association for Computing Machinery[7]
- 2022 – Fellow, AAAS
References
edit- ^ "Publications - Dana Nau". UMD Department of Computer Science. July 22, 2022. Retrieved March 24, 2009.
- ^ Nau, Dana (1982). "An investigation of the causes of pathology in games". Artificial Intelligence. 19 (3): 257–278. doi:10.1016/0004-3702(82)90002-9.
- ^ "Simple Hierarchical Ordered Planner". cs.umd.edu. Retrieved November 8, 2024.
- ^ "Automated Planning and Acting".
- ^ "Elected AAAI Fellows".
- ^ "2022 AAAS Fellows approved by the AAAS Council". Science. 379 (6634): 768–772. February 24, 2023. Bibcode:2023Sci...379..768.. doi:10.1126/science.adh2210. PMID 36821656. S2CID 240657197.
- ^ ACM Names Fellows for Computing Advances that Are Transforming Science and Society Archived 2017-09-15 at the Wayback Machine, Association for Computing Machinery, accessed 2013-12-10.
External links
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