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.

Item Type:	Refereed Conference Paper
Keywords:	artificial intelligence, biology, instruments, Markov processes, space vehicles, uncertainty
Research Division:	Information and Computing Sciences
Research Group:	Distributed Computing
Research Field:	Ubiquitous Computing
Objective Division:	Information and Communication Services
Objective Group:	Computer Software and Services
Objective Field:	Application Tools and System Utilities
UTAS Author:	Nixon, P (Professor Paddy Nixon)
ID Code:	97695
Year Published:	2010
Deposited By:	Information and Communication Technology
Deposited On:	2015-01-08
Last Modified:	2015-01-28
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