Contribuţii la achiziţia şi structurarea cunoştinţelor în sisteme inteligente pentru diagnoza defectelor
Bibliografie
[81]. Langton, C. (1989). Artificial Life, Redwood City, CA: Addison-Wesley
[82]. Lawler, E.L., & Wood, D.E. (1966). Branch and bound methods: a survey.
Operations Research, 14, pp:699-719.
[83]. Leake, D. B., Kinley, A., & Wilson, D. (1996a). CBR: Experiences, Lessons and
Future Directions. AAAI Press, MIT Press. Chapter Learning to improve Case
Adaptation by Introspective Reasoning and CBR, pp. 185–196.
[84]. Leake, D. B., Kinley, A., & Wilson, D. (1996b). Linking adaptation and similarity
learning. Eighteenth Annual Conference of the Cognitive Science Society.
[85]. Leake, D., and Dial, S. A. (2008). Using case provenance to propagate feedback to
cases and adaptations. Proceedings of 9th European Conference on Advances in
CBR, pp. 89–103, Springer-verlag., Trier, Germany.
[86]. Leinberger, W., Karypis, G., & Kumar, V., Load Balancing Across NearHomogeneousMulti-Resource Servers. Proceedings. 9thHeterogeneous Computing
Workshop (HCW 2000) Cancun, Mexico, 2000.
[87]. Lewis, L. (1993). A case-based reasoning approach to the resolution of faults in
communications networks, in: Hegering, H.G., Yemini, Y. (Eds.), Integrated
Network Management III, North-Hollan