Utilizing concept maps to improve human-agent collaboration within a recognition-primed decision model

Timothy Hanratty, Robert J. Hammell, John Yen, Xiaocong Fan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

In our ever expanding network-centric, service-oriented environments, human-agent collaboration is becoming increasingly more important to the success of future automated decision support models. Effective information retrieval, information analysis, information management and presentation will rely on stronger collaboration between the user (human) and their automated decision assistants (agents). This paper explores the utility of concept maps as an effective medium for improving human-agent collaboration within the scope of a naturalistic decision making (NDM) model; specifically the agent-based R-CAST system derived from Klein's Recognition-Primed Decisions (RPD) Model.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2007
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages116-120
Number of pages5
ISBN (Print)0769530273, 9780769530277
DOIs
StatePublished - Jan 1 2007
EventIEEE Computer Society Technical Committee on Intelligent Informatics(TCII) - Fremont, CA, United States
Duration: Nov 2 2007Nov 5 2007

Publication series

NameProceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2007

Other

OtherIEEE Computer Society Technical Committee on Intelligent Informatics(TCII)
Country/TerritoryUnited States
CityFremont, CA
Period11/2/0711/5/07

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

Fingerprint

Dive into the research topics of 'Utilizing concept maps to improve human-agent collaboration within a recognition-primed decision model'. Together they form a unique fingerprint.

Cite this