Abstract
| Language | English |
|---|---|
| Pages | 102-111 |
| Number of pages | 9 |
| Journal | AI Magazine |
| Volume | 22 |
| Issue number | 3 |
| Publication status | Published - 2001 |
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Keywords
- planning technology
- scheduling
- static domain analysis
- stan4
- artificial intelligence
Cite this
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STAN4 : a hybrid planning strategy based on subproblem abstraction. / Fox, Maria; Long, Derek.
In: AI Magazine, Vol. 22, No. 3, 2001, p. 102-111.Research output: Contribution to journal › Article
TY - JOUR
T1 - STAN4
T2 - AI Magazine
AU - Fox, Maria
AU - Long, Derek
PY - 2001
Y1 - 2001
N2 - Planning domains often feature subproblems such as route planning and resource handling. Using static domain analysis techniques, we have been able to identify certain commonly occurring subproblems within planning domains, making it possible to abstract these subproblems from the overall goals of the planner and deploy specialized technology to handle them in a way integrated with the broader planning activities. Using two such subsolvers our hybrid planner, stan4, participated successfully in the Fifth International Conference on Artificial Intelligence Planning and Scheduling (AIPS'00) planning competition.
AB - Planning domains often feature subproblems such as route planning and resource handling. Using static domain analysis techniques, we have been able to identify certain commonly occurring subproblems within planning domains, making it possible to abstract these subproblems from the overall goals of the planner and deploy specialized technology to handle them in a way integrated with the broader planning activities. Using two such subsolvers our hybrid planner, stan4, participated successfully in the Fifth International Conference on Artificial Intelligence Planning and Scheduling (AIPS'00) planning competition.
KW - planning technology
KW - scheduling
KW - static domain analysis
KW - stan4
KW - artificial intelligence
UR - http://www.aaai.org/Magazine/magazine.php
UR - http://www.aaai.org/ojs/index.php/aimagazine/article/view/1577
M3 - Article
VL - 22
SP - 102
EP - 111
JO - AI Magazine
JF - AI Magazine
SN - 0738-4602
IS - 3
ER -