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Please use this identifier to cite or link to this item: http://hdl.handle.net/1860/2038

Title: Bridging the lesson distribution gap
Authors: Aha, David
Weber, Rosina O.
Muñoz-Avila, Héctor
Breslow, Leonard
Gupta, Kalyan Moy
Issue Date: Aug-2001
Publisher: Elsevier
Citation: Paper presented at The 17th International Joint Conference on Artificial Intelligence, IJCAI 2001, Seattle, WA: pp. 987-992.
Abstract: Many organizations employ lessons learned (LL) processes to collect, analyze, store, and distribute, validated experiential knowledge (lessons) of their members that, when reused, can substantially improve organizational decision processes. Unfortunately, deployed LL systems do not facilitate lesson reuse and fail to bring lessons to the attention of the users when and where they are needed and applicable (i.e., they fail to bridge the lesson distribution gap). Our approach for solving this problem, named monitored distribution, tightly integrates lesson distribution with these decision processes. We describe a case-based implementation of monitored distribution (ALDS) in a plan authoring tool suite (HICAP). We evaluate its utility in a simulated military planning domain. Our results show that monitored distribution can significantly improve plan evaluation measures for this domain.
URI: http://hdl.handle.net/1860/2038
Appears in Collections:Faculty Research and Publications (IST)

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