Bridging the Lesson Distribution Gap

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. 1

Cite

Text

Aha et al. "Bridging the Lesson Distribution Gap." International Joint Conference on Artificial Intelligence, 2001.

Markdown

[Aha et al. "Bridging the Lesson Distribution Gap." International Joint Conference on Artificial Intelligence, 2001.](https://mlanthology.org/ijcai/2001/aha2001ijcai-bridging/)

BibTeX

@inproceedings{aha2001ijcai-bridging,
  title     = {{Bridging the Lesson Distribution Gap}},
  author    = {Aha, David W. and Weber, Rosina and Muñoz-Avila, Héctor and Breslow, Len and Gupta, Kalyan Moy},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2001},
  pages     = {987-992},
  url       = {https://mlanthology.org/ijcai/2001/aha2001ijcai-bridging/}
}