A multi-agent system for acquiring and sharing lessons learned

Authors:
Cesar A. Tacla;Jean-Paul Barthès
Affiliations:
CNRS UMR 6599 HEUDYASIC, Computer Science Department, University of Technology of Compiègne, BP 20529-60205 Complègne Cedex, France;CNRS UMR 6599 HEUDYASIC, Computer Science Department, University of Technology of Compiègne, BP 20529-60205 Complègne Cedex, France
Venue:
Computers in Industry - Special issue: Knowledge sharing in collaborative design environments
Year:
2003

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Abstract

This paper presents a multi-agent system for knowledge management (KM) in research and development (R&D) projects. R&D teams have no time to organize project information, nor to articulate the rationale behind the actions that generated the information. Our aim is to provide a system for helping team members to explicit knowledge, and to allow them to share their experiences, i.e. lessons learned (LL), without asking them too much extra-work. The article focuses on how we intend to help the team members to feed the system with LL, using the operations they perform on desktop computers, and how we intend to exploit the LL by using a case-based reasoning engine. We have been developing a prototype of such a KM system for a cooperative project.