A Methodology For The Assessment Of Buddy-Agents


Ali R. Montazemi
Xiaoqing Li


Computer-based information systems connected to high-speed communication networks provide increasingly rapid access to a wide variety of data resources. However, this connectivity to data resources burdens decision-makers with the need to access and analyze large volumes of data to support their decision-making processes. Without effective guidance in decision-making, access to data resources provides only minor benefits. Intelligent agents are expected to act like human assistants and support complex decision processes, either by anticipating the information requirements of the decision makers or by autonomously performing a specific set of tasks. In this article, we provide a methodology based on fuzzy-set methodology for the assessment of buddy-agents in a distributed, multi-agent information system environment that supports complex decision problems. Our findings from an assessment of the methodology for the selection of common stocks support the viability of the methodology proposed.

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May, 2004

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