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Please use this identifier to cite or link to this item: http://hdl.handle.net/10197/1207
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Title: An agent-based approach to component management
Author: Lillis, David
Collier, Rem
Dragone, Mauro
O'Hare, G. M. P. (Greg M. P.)
Date: May-2009
Publisher: International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Is part of: Decker ...et al. (eds.). Proceedings of 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009)
Type of material: Conference Publication
Abstract: This paper details the implementation of a software framework that aids the development of distributed and self-configurable software systems. This framework is an instance of a novel integration strategy called SoSAA (SOcially Situated Agent Architecture), which combines Component-Based Software Engineering and Agent-Oriented Software Engineering, drawing its inspiration from hybrid agent control architectures. The framework defines a complete construction process by enhancing a simple component-based framework with reasoning and self-awareness capabilities through a standardized interface. The capabilities of the resulting framework are demonstrated through its application to a non-trivial Multi Agent System (MAS). The system in question is a pre-existing Information Retrieval (IR) system that has not previously taken advantage of CBSE principles. In this paper we contrast these two systems so as to highlight the benefits of using this new hybrid approach. We also outline how component-based elements may be integrated into the Agent Factory agent-oriented application framework.
Conference details: Eighth International Conference on Autonomous Agents and MultiAgent Systems, May, 10–15, 2009, Budapest
Web link to reference this item: http://hdl.handle.net/10197/1207
Subject Heading: Distributed artificial intelligenceSoftware engineeringMultiagent systems
Other web versions: Publisher's version
Status of Item: Peer reviewed
Availability: Full text available
Appears in Collections:CSI Research Collection
CLARITY Research Collection



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