- Abstract:
- In this paper, we outline the requirements of a planning and decision aid to support US Army small unit operations in urban terrain and show how AI planning technologies can be exploited in that context. The work is a rare example of a comprehensive use of AI technologies across the whole planning lifecycle, set in a realistic application in which the actual user community set the requirements. The phases involved include:
* Domain knowledge elicitation
* Rich plan representation and use
* Hierarchical Task Network Planning
* Detailed constraint management
* Goal structure-based plan monitoring
* Dynamic issue handling
* Plan repair in low and high tempo situations
* Interfaces for users with different roles
* Management of planning and execution workflow
- Copyright:
- 2000, American Association of Artificial Intelligence (http://www.aaai.org/).
- The U.S. Government and the University of Edinburgh are authorised to reproduce and distribute reprints for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing official policies or endorsements, either express or implied, of the Defense Advanced Research Projects Agency, the Air Force Research Laboratory, the US Government or the University of Edinburgh.
- Links To Paper
- No links available
- Bibtex format
- @InProceedings{EDI-INF-RR-0006,
- author = {
Austin Tate
and John Levine
and Peter Jarvis
and Jeffrey Dalton
},
- title = {Using AI Planning Techniques for Army Small Unit Operations},
- book title = {Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling Systems (AIPS 2000)},
- year = 1999,
- month = {Dec},
- }
|
