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The Washington Post, some weekday between October and December, 1999.

The Washington Post, some weekday between October and December, 1999. Categorizing Intelligent Lessons Learned Systems. Rosina Weber, David W. Aha, Irma Becerra-Fernandez. Computer Science, U. of Wyoming, Navy Center for Applied Research in AI, Naval Research Laboratory.

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The Washington Post, some weekday between October and December, 1999.

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  1. The Washington Post, some weekday between October and December, 1999.

  2. Categorizing Intelligent Lessons Learned Systems Rosina Weber, David W. Aha, Irma Becerra-Fernandez Computer Science, U. of Wyoming, Navy Center for Applied Research in AI, Naval Research Laboratory Rosina Weber/ILLS AAAI’00

  3. Goals & Perspectives • AI research perspective • LLS are organizational systems • Organizational goals and restrictions • Problems in promoting knowledge sharing • How can AI help? • DOD, DOE, Space agencies • Survey, categorization • Design, develop, & deploy issues

  4. Consistency • Redundancy • Correctness • Successes • Failures • Valid Defining Lessons learned Work practice Successes/Failures Valid Applicable Generate an impact • Working experiences  work practice • Generate impact • Applicable to a task/decision (process)

  5. Two step categorization • LL process: • Collect • Verify • Store • Disseminate • Reuse • LL systems

  6. Lessons Learned Process

  7. interactivecollect ongoing proactive collect CALVIN active (military) collect CALL, JCLL, NLLS active (scan) collect ESA LL, Lockheed Martin LL, Project Hanford LL, ESH LL Program Collect reactive collect COIN, NASDA after action collect Alenia, Canadian Army LL Centre, ESA, JCLL, Marine Corps, NLLS passive collect others

  8. active disseminate ALDS CALVIN reactive disseminate ACPA proactive disseminate ACPA Disseminate passive disseminate AFCKS, CALL, ESA LL, JCLL, RECALL, AMEDD, NLLS, NAWCAD, ALLCARS, Alenia, Eureka, SELLS members broadcasting disseminate Canadian Army LL Centre, DOE Corporate, Federal Transit Administration LL Program, Marine Corps LL System, NLLS active casting disseminate CALL, DOE Corporate

  9. Reuse browsable recommendation ACPA Standalone . . . executable recommendation ALDS

  10. Two step categorization • LL process • LL systems • Content • Role • Purpose and scope • Organization type, duration • Attributes and format • Architecture

  11. Content • Pure Eureka (XEROX), AirForceCKS, JCLL, RECALL • Hybrid • CALL, DOE corporate, NLLS, • NAWCAD, ESA LL

  12. Role • Planning JCLL, Marine Corps, NAWCAD, AMEDD, Canadian Army • Technical • Eureka, DOE Corporate, Alenia (Italian) • Both • RECALL, CNES

  13. Purpose & scope • Start design with scope • Organization subsystem • Purpose of the subsystem • Subsystem  processes • Which lessons to include

  14. Organization Type • rigid • flexible • Duration • permanent • temporary

  15. Attributes & Format Typical: • Observation, discussion, lessons learned: textual • Desired: • Applicable task (process) • Conditions necessary for reuse • The lesson (work practice)

  16. Architecture • Standalone: all implemented LL systems • Embedded to the process: • CALVIN, ACPA, ALDS

  17. Conclusions (DDD) • Identify the TYPE of your organization ; • Define the DURATION for the system; • Define the SCOPE & PURPOSE; • Identify the CONTENT; • Identify the ROLE; • Define ATTRIBUTES & FORMAT; • Design an embedded ARCHITECTURE; • DDD methods for COLLECT; • DDD methods for VERIFY & STORE; • DDD methods for DISSEMINATE & REUSE.

  18. Research Directions • elicitation tool • planning audience • technical audience • different processes and embedded architectures • extraction tool (from text)

  19. Lessons learned session Watch out for Harry’s lessons!! NBC’s sitcom has a lessons learned session in every episode when characters sit on the roof.

  20. Lessons learned and other knowledge artifacts

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