Matrix-agent framework: A virtual platform for multi-agents

• Published in: Journal of systems science and systems engineering Vol. 15; no. 4; pp. 436 - 456
• Main Authors: Zhang, Hao Lan, Leung, Clement H.C., Raikundalia, Gitesh K.
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer Nature B.V 01.12.2006; School of Computer Science and Mathematics, Victoria University PO Box 14428 Melbourne City MC 8001 Australia
• Subjects: Data processing; Decision support systems; Multiagent systems; Network topologies; Multi-agent; virtual agent society; agent topology analysis; AOCD; DSS
• ISSN: 1004-3756; 1861-9576
• DOI: 10.1007/s11518-006-5028-0

Multi-agent technology has been applied extensively to many areas, including Decision Support Systems (DSS). However, the applications of multi-agent technology in DSS are still very preliminary. Most of the current agent frameworks, such as middle-agent-based or agent-facilitator-based frameworks, are basically agent-to-agent model. These agent-based frameworks often neglect the living environment for agents and they suffer from: (i) inability to adapt to the environment, (ii) inability to self-upgrade, and (iii) inefficiency in information acquisition. Here, we introduce a recently proposed multi-agent framework, namely Agent-based Open Connectivity for Decision Support Systems (AOCD). In this new framework, the communication and cooperation between agents are through a key component, the Matrix, which provides a virtual platform for agents. We use a unified Matrices framework to solve the bottleneck problem in the AOCD framework. Our experimental results based on different agent network topologies indicate that the hybrid topology presents superior performance compared with the centralised and decentralised topologies.