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| Content Provider | Springer Nature Link |
|---|---|
| Author | Horling, Bryan Lesser, Victor Vincent, Régis Wagner, Thomas |
| Copyright Year | 2005 |
| Abstract | Real-time control has become increasingly important as technologies are moved from the lab into real world situations. The complexity associated with these systems increases as control and autonomy are distributed, due to such issues as temporal and ordering constraints, shared resources, and the lack of a complete and consistent world view. In this paper we describe a soft real-time architecture designed to address these requirements, motivated by challenges encountered in a real-time distributed sensor allocation environment. The system features the ability to generate schedules respecting temporal, structural and resource constraints, to merge new goals with existing ones, and to detect and handle unexpected results from activities. We will cover a suite of technologies being employed, including quantitative task representation, alternative plan selection, partial-order scheduling, schedule consolidation and execution and conflict resolution in an uncertain environment. Technologies which facilitate on-line real-time control, including meta-level accounting, schedule caching and variable time granularities are also discussed. |
| Starting Page | 35 |
| Ending Page | 91 |
| Page Count | 57 |
| File Format | |
| ISSN | 13872532 |
| Journal | Autonomous Agents and Multi-Agent Systems |
| Volume Number | 12 |
| Issue Number | 1 |
| e-ISSN | 15737454 |
| Language | English |
| Publisher | Kluwer Academic Publishers |
| Publisher Date | 2005-09-26 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | agent control scheduling soft real-time resource management Artificial Intelligence (incl. Robotics) Software Engineering/Programming and Operating Systems Software Engineering User Interfaces and Human Computer Interaction Computing Methodologies |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence |
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