What question did this study set out to answer?

To examine how autonomous interface agents can assist users in managing excessive digital information and repetitive computing tasks.

July 1, 1994Communications of the ACM2,331 citations

Agents that reduce work and information overload

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PMPattie Maes

Key Points

To examine how autonomous interface agents can assist users in managing excessive digital information and repetitive computing tasks.
Analyzed the design and implementation of learning software agents integrated into user interfaces.
Evaluated agent training mechanisms, including passive user observation, direct feedback, explicit instructions, and multi-agent communication.
Interface agents progressively adapt to individual preferences over time, enabling proactive assistance and routine task automation without requiring manual rule configuration.
Collaborative learning among peer agents significantly accelerates the acquisition of competent decision-making and filtering capabilities across diverse applications.

Abstract

article Free Access Share on Agents that reduce work and information overload Author: Pattie Maes MIT Media Lab., Cambridge, MA MIT Media Lab., Cambridge, MAView Profile Authors Info & Claims Communications of the ACMVolume 37Issue 7July 1994 pp 30–40https://doi.org/10.1145/176789.176792Published:01 July 1994Publication History 26citation8,051DownloadsMetricsTotal Citations26Total Downloads8,051Last 12 Months137Last 6 weeks19 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

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Cite This Study

Pattie Maes (1994) studied this question.

synapsesocial.com/papers/69fd5f72ea4a61241c5d1f4c https://doi.org/10.1145/176789.176792

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July 1, 1994Communications of the ACM2,331 citations

Agents that reduce work and information overload

View Full Paper

PMPattie Maes

Key Points

To examine how autonomous interface agents can assist users in managing excessive digital information and repetitive computing tasks.
Analyzed the design and implementation of learning software agents integrated into user interfaces.
Evaluated agent training mechanisms, including passive user observation, direct feedback, explicit instructions, and multi-agent communication.
Interface agents progressively adapt to individual preferences over time, enabling proactive assistance and routine task automation without requiring manual rule configuration.
Collaborative learning among peer agents significantly accelerates the acquisition of competent decision-making and filtering capabilities across diverse applications.

Abstract

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View Full Paper

Cite This Study

Pattie Maes (1994) studied this question.

synapsesocial.com/papers/69fd5f72ea4a61241c5d1f4c https://doi.org/10.1145/176789.176792

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