Donald W. Loveland
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Donald W. Loveland | |
---|---|
Born | Rochester, New York |
December 26, 1934
Fields | Computer science |
Institutions | Duke University |
Alma mater | New York University |
Thesis | Recursively Random Sequences (1964) |
Doctoral advisors | Peter Ungar, Martin David Davis |
Doctoral students | Owen Astrachan, Robert Daley, Timothy Gegg-Harrison, Susan Gerhart, David Mutchler, C. Ramu Reddy, David Reed, Marco Valtorta |
Known for | DPLL algorithm |
Notable awards | Herbrand Award 2001 |
Donald W. Loveland (born December 26, 1934 in Rochester, New York)[1] is a professor emeritus of computer science at Duke University who specializes in artificial intelligence.[2]
He graduated from Oberlin College in 1956, received a Masters degree from the Massachusetts Institute of Technology in 1958 and a Ph.D. from New York University in 1964.[3] Loveland received the Herbrand Award in 2001.[3] He is well-known for the Davis–Putnam–Logemann–Loveland algorithm.[4]
Bibliography
- Genetic Algorithms + Data Structures = Evolution Programs by Yun Peng, J. A. Reggia, D. W. Loveland, S. Amarel, A. Biermann ISBN 0-387-55387-8
- 6th Conference on Automated Deduction by D. W. Loveland ISBN 3-540-11558-7
- Nonmonotonic Logic: Context-Dependent Reasoning by Yun Peng, J. A. Reggia, D. W. Loveland, S. Amarel, A. Biermann ISBN 0-387-56448-9
References
- ↑ Loveland, D.W.; Stickel, M.E.; "A Hole in Goal Trees: Some Guidance from Resolution Theory". In Proceedings of IEEE Trans. Computers. 1976, 335-341.
- ↑ Duke University personal page
- ↑ 3.0 3.1 Curriculum Vitae
- ↑ Lua error in package.lua at line 80: module 'strict' not found.
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Categories:
- 20th-century American mathematicians
- 21st-century American mathematicians
- 1934 births
- Living people
- Oberlin College alumni
- Massachusetts Institute of Technology alumni
- New York University alumni
- Duke University faculty
- American computer scientists
- Artificial intelligence researchers
- American mathematician stubs