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The Method Engineering Process for Multi-Agent System Development
Adelaide, Australia January 23-January 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WKDD.2008.26First International Workshop on Knowl ...
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Xue Xiao, Zhang Xueyan, "The Method Engineering Process for Multi-Agent System Development," International Workshop on Knowledge Discovery and Data Mining, pp. 160-163, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008.
 
 
BibTex
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@article{ 10.1109/WKDD.2008.26,
author = {Xue Xiao and Zhang Xueyan},
title = {The Method Engineering Process for Multi-Agent System Development},
journal ={International Workshop on Knowledge Discovery and Data Mining},
volume = {0},
year = {2008},
isbn = {0-7695-3090-7},
pages = {160-163},
doi = {http://doi.ieeecomputersociety.org/10.1109/WKDD.2008.26},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - International Workshop on Knowledge Discovery and Data Mining
TI - The Method Engineering Process for Multi-Agent System Development
SN - 0-7695-3090-7
SP160
EP163
A1 - Xue Xiao,
A1 - Zhang Xueyan,
PY - 2008
VL - 0
JA - International Workshop on Knowledge Discovery and Data Mining
ER -
 
The agent-oriented (AO) methodology is an effective means for constructing distributed systems. Despite a great deal of research, a number of challenges still exist before making agent-based computing a widely accepted paradigm in software engineering practice. In order to solve the problem of "difficult to implement", the paper presents a method engineering development process for facilitating building up new agent system by reusing method meta models and design patterns. As the supporting tool, the hierarchical development architecture(HDA) plays a key role in the process. To exemplify its feasibility and effectiveness, the construction of C4I system is presented as a case study.
Citation:
Xue Xiao, Zhang Xueyan, "The Method Engineering Process for Multi-Agent System Development," wkdd, pp.160-163, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008
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