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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/5623
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dc.contributor.authorLi, Xiaoqingen_US
dc.contributor.authorMontazemi, Ali Rezaen_US
dc.contributor.authorMcMaster University, Michael G. DeGroote School of Businessen_US
dc.date.accessioned2014-06-17T20:37:16Z-
dc.date.available2014-06-17T20:37:16Z-
dc.date.created2013-12-23en_US
dc.date.issued2001-03en_US
dc.identifier.otherdsb/8en_US
dc.identifier.other1007en_US
dc.identifier.other4944027en_US
dc.identifier.urihttp://hdl.handle.net/11375/5623-
dc.description<p>28 p. : ; Includes bibliographical references: leaves 25-27. ; "March 2001"</p>en_US
dc.description.abstract<p>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 the need to access and analyze a large volume of data to support their decision making processes. Without effective decisional guidance, access to data resources provides only a minor benefit to decision-makers. Intelligent agents are expected to act like human-assistants in support of complex decision processes 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 for assessment of buddy-agents in a multi-agent information system environment in support of complex decision problems. Our findings from an empirical assessment of the methodology that was used to support common stocks selection among investors support the viability of the proposed methodology.</p>en_US
dc.relation.ispartofseriesResearch and working paper series (Michael G. DeGroote School of Business)en_US
dc.relation.ispartofseriesno. 452en_US
dc.subjectBusinessen_US
dc.subjectBusinessen_US
dc.subject.lccIntelligent agents (Computer software) Intelligent agents (Computer software) > Research > Methodologyen_US
dc.titleA methodology for the assessment of buddy-agentsen_US
dc.typearticleen_US
Appears in Collections:DeGroote School of Business Working Paper Series

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