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 |
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ASJC Scopus subject areas
- Software
Cite this
Refinement planning : Status and prospectus. / Kambhampati, Subbarao.
Proceedings of the National Conference on Artificial Intelligence. ed. / Anon. Vol. 2 Menlo Park, CA, United States : AAAI, 1996. p. 1331-1336.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Refinement planning
T2 - Status and prospectus
AU - Kambhampati, Subbarao
PY - 1996
Y1 - 1996
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=0030373771&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0030373771
VL - 2
SP - 1331
EP - 1336
BT - Proceedings of the National Conference on Artificial Intelligence
A2 - Anon, null
PB - AAAI
CY - Menlo Park, CA, United States
ER -