Abstract
Most current-day AI planning systems operate by iteratively refining a partial plan until it meets the goal requirements. In the past five years, significant progress has been made in our understanding of the spectrum and capabilities of such refinement planners. In this talk, I will summarize this understanding in terms of a unified framework for refinement planning and discuss several current research directions.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the National Conference on Artificial Intelligence |
| Editors | Anon |
| Place of Publication | Menlo Park, CA, United States |
| Publisher | AAAI |
| Pages | 1331-1336 |
| Number of pages | 6 |
| Volume | 2 |
| State | Published - 1996 |
| Event | Proceedings of the 1996 13th National Conference on Artificial Intelligence. Part 2 (of 2) - Portland, OR, USA Duration: Aug 4 1996 → Aug 8 1996 |
Other
| Other | Proceedings of the 1996 13th National Conference on Artificial Intelligence. Part 2 (of 2) |
|---|---|
| City | Portland, OR, USA |
| Period | 8/4/96 → 8/8/96 |
ASJC Scopus subject areas
- Software