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Using Iterative Repair to Improve the Responsiveness of Planning and Scheduling
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| dc.contributor.author | Chien, S. | en_US |
| dc.contributor.author | Knight, R. | en_US |
| dc.contributor.author | Stechert, A. | en_US |
| dc.contributor.author | Sherwood, R. | en_US |
| dc.contributor.author | Rabideau, G. | en_US |
| dc.date.accessioned | 2004-09-23T17:31:41Z | |
| dc.date.available | 2004-09-23T17:31:41Z | |
| dc.date.issued | 2000-04-14 | en_US |
| dc.identifier.citation | Artificial Intelligence Planning and Scheduling | en_US |
| dc.identifier.citation | Breckenridge, CO, USA | en_US |
| dc.identifier.clearanceno | 00-0277 | en_US |
| dc.identifier.uri | http://hdl.handle.net/2014/13902 | |
| dc.description.abstract | The majority of planning and scheduling research has focused on batch-oriented models of planning. | en_US |
| dc.format.extent | 988883 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en_US | |
| dc.subject.other | Artificial Intelligence planning scheduling execution | en_US |
| dc.title | Using Iterative Repair to Improve the Responsiveness of Planning and Scheduling | en_US |
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JPL TRS 1992+
JPL TRS 1992+