Robot share: a framework for robot knowledge sharing

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Publication Type thesis
School or College College of Engineering
Department Computing
Author Fan, Xiuyi
Title Robot share: a framework for robot knowledge sharing
Date 2009-05
Description Knowledge representation is a traditional field in artificial intelligence. Researchers have developed various ways to represent and share information among intelligent agents. Agents that share resources, data, information, and knowledge perform better than agents working alone. However, previous research also reveals that sharing knowledge among a large number of entities in an open environment is a problem yet to be solved. Intelligent robots are designed and produced by different manufacturers. They have various physical attributes and employ different knowledge representations. Therefore, any nonstandard or non-widely-adopted technology is unsuitable to provide a satisfactory solution to the knowledge sharing problem. In this research, we pose robot knowledge sharing as an activity to be developed in an open environment - the World Wide Web. Just as search engines like Google provide enormous power for information exchange and sharing for humans, we believe a searching mechanism designed for intelligent agents can provide a robust approach for sharing knowledge among robots. We have developed (1) a knowledge representation for robots that allows Internet access, (2) a knowledge organization and search indexing engine, and (3) a query/reply mechanism between robots and the search engine.
Type Text
Publisher University of Utah
Subject Robots; Artificial intelligence
Dissertation Institution University of Utah
Dissertation Name MS
Language eng
Relation is Version of Digital reproduction of "Robot share : a framework for robot knowledge sharing" J. Willard Marriott Library Special Collections, TJ7.5 2009 .F36
Rights Management © Xiuyi Fan
Format Medium application/pdf
Format Extent 118.106 bytes
Identifier us-etd2,106226
Source Original: University of Utah J. Willard Marriott Library Special Collections
Conversion Specifications Orginal scanned on Epson GT-30000 as 400 dpi to pdf using ABBYY FineReader 9.0 Professional Edition.
ARK ark:/87278/s6w95qwx
Setname ir_etd
ID 194011
Reference URL https://collections.lib.utah.edu/ark:/87278/s6w95qwx