Introspective Learning to Build Case-Based Reasoning
Wikipedia defines introspection as “the self-observation of one’s mental processes.” Introspective learning occurs when an agent applies self-observation to its reasoning processes in order to improve its problem-solving performance. Case-based reasoning solves problems by retrieving stored experiences of previous problem-solving that are similar to the new problem, and reusing the solutions of these similar experiences. Applied to case-based reasoning, introspective learning observes and critiques the reasoning that has been applied. Therefore, it analyzes what experience is retrieved, why it is retrieved, and how the experience is reused, so that it may consider and evaluate alternative reasoning options that might achieve preferable problem-solving activity. The outcome of introspective learning for case-based reasoning is an adaptation of one or more of the core components of...
- Aamodt, A., & Plaza, E. (1994). Case-based reasoning: Foundational issues, methodological variations, and system approaches. Artificial Intelligence Communications, 7(1), 39–59. IOS Press. http://www.idi.ntnu.no/∼agnar/publications/aicom-94.pdf. Accessed 18 Nov 2010.
- Fox, S., & Leake, D. B. (1995). Using introspective reasoning to refine indexing, Proceedings of the 14th International Joint Conference on Artificial Intelligence (pp. 391–397). http://ijcai.org/PastProceedings/IJCAI-95-VOL1/pdf/052.pdf. Accessed 18 Nov 2010.