Donald W. Loveland
| Donald W. Loveland | |
|---|---|
| Born |
December 26, 1934 Rochester, New York |
| 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
- 1 2 Curriculum Vitae
- ↑ Davis, Martin; Logemann, George; Loveland, Donald (1962). "A Machine Program for Theorem Proving". Communications of the ACM 5 (7): 394–397. doi:10.1145/368273.368557.
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