| dc.contributor.author | Vassev, Emil | |
| dc.contributor.author | Hinchey, Mike | |
| dc.contributor.author | Nixon, Paddy | |
| dc.date.accessioned | 2011-02-04T12:28:04Z | |
| dc.date.available | 2011-02-04T12:28:04Z | |
| dc.date.issued | 2010 | |
| dc.identifier.uri | http://hdl.handle.net/10344/746 | |
| dc.description | peer-reviewed | en_US |
| dc.description.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. | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | IEEE Computer Society | en_US |
| dc.relation.ispartofseries | 5th NASA/ESA Conference on Adaptive Hardware and Systems (AHS) 2010;pp. 83 - 90 | |
| dc.relation.uri | http://dx.doi.org/10.1109/AHS.2010.554627 | |
| dc.rights | ©2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. | en_US |
| dc.subject | swarm intellegence | en_US |
| dc.subject | space exploration | en_US |
| dc.title | A formal approach to self-configurable swarm-based space-exploration systems | en_US |
| dc.type | Conference item | en_US |
| dc.type.supercollection | all_ul_research | en_US |
| dc.type.supercollection | ul_published_reviewed | en_US |
| dc.type.restriction | none | en |
| dc.contributor.sponsor | SFI |