Selecting a methodology in Multi-Agent Systems - A Practical and Quasi-Technical Analysis of Agent-based, Object Oriented and Knowledge Engineering-based methodologies.

Authors(2) :-Kevin Mugoye, Simon Ruoro

As recognition of agents’ technology registers steady improvement over years, there is an emergent need for practical methods for developing agent applications. Agent-Oriented Software Engineering (AOSE) methodologies were proposed to develop complex distributed system grounded upon the agent paradigm. Initially, the challenge was the lack of mature development methodologies for agent-based systems, efforts in the right direction to address the problem resulted in the proliferation of methodologies, which presents a new challenge that is, practitioners are challenged in that they need to select a methodology from a large number of existing methodologies. The literature in this paper suggests a necessity to the understanding of the classification of AOSE methodologies. We advocate for a view that is in twofold, first, practitioners need to first understand in a wide sense the categories of AOSE methodologies, so as to correctly link it to their intended agent solution, secondly, identify a methodology considering the availability of support features such as maturity, availability of documentation and support tools.

Authors and Affiliations

Kevin Mugoye
Department of Computer Science, Maseno University, Private Bag, Maseno, Kenya
Simon Ruoro
Department of Computer Science, Maseno University, Private Bag, Maseno, Kenya

Multi-Agent System, Agent Based Methodologies, Artificial Intelligence

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Publication Details

Published in : Volume 2 | Issue 3 | May-June 2017
Date of Publication : 2017-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 661-669
Manuscript Number : CSEIT1723207
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Kevin Mugoye, Simon Ruoro, "Selecting a methodology in Multi-Agent Systems - A Practical and Quasi-Technical Analysis of Agent-based, Object Oriented and Knowledge Engineering-based methodologies. ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 3, pp.661-669, May-June-2017.
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