Abstract
Intelligent swarms draw their inspiration from biology where many simple entities act independently, but when grouped, they appear to be highly organized. NASA is currently investigating swarm-based technologies for the development of prospective exploration missions to explore regions of space where a single large spacecraft would be impractical. The main emphasis of this research is to develop algorithms and prototyping models for self-managing swarm-based space-exploration systems. This article presents our work on formally modeling self-configuring behavior in such systems. We present a formal model for team formation based on Partially Observable Markov Decision Processes and Discrete Time Markov Chains along with formal models for planning and scheduling.
| Original language | English |
|---|---|
| Title of host publication | Unknown Host Publication |
| Publisher | IEEE |
| Pages | 83-90 |
| Number of pages | 8 |
| ISBN (Print) | 978-1-4244-5887-5 |
| DOIs | |
| Publication status | Published (in print/issue) - 2010 |
| Event | Proceedings of the 2010 NASA/ESA Conference on Adaptive Hardware and Systems - Anaheim, CA, USA Duration: 1 Jan 2010 → … |
Conference
| Conference | Proceedings of the 2010 NASA/ESA Conference on Adaptive Hardware and Systems |
|---|---|
| Period | 1/01/10 → … |
Keywords
- artificial intelligence
- biology
- instruments
- Markov processes
- space vehicles
- uncertainty
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