Case-Based reasoning: Foundational issues, methodological variations, and system approaches

AI Communications

Volumn 7, Issue 1, 1994, Pages 39-59

  Agnar, Aamodt ^a   Plaza, Enric ^b  

^a NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

^b ARTIFICIAL INTELLIGENCE RESEARCH INSTITUTE IIIA CSIC   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

INFERENCE ENGINES; KNOWLEDGE BASED SYSTEMS;

CASE BASED REASONING; FOUNDATIONAL ISSUES; METHODOLOGICAL VARIATIONS;

ARTIFICIAL INTELLIGENCE;

EID: 0028401306     PISSN: 09217126     EISSN: None     Source Type: Journal    
DOI: 10.3233/AIC-1994-7104     Document Type: Article

References (75)

1. Aamodt, A., (1989): Towards robust expert systems that learn from experience - an architectural framework. In: John Boose, Brian Gaines, Jean-Gabriel Ganascia (eds.): EKAW-89; Third European Knowledge Acquisition for Knowledge-Based Systems Workshop, Paris, July 1989, 311-326.
2. Aamodt, A. (1991): A knowledge-intensive approach to problem solving and sustained learning, Ph.D. dissertation, University of Trondheim, Norwegian Institute of Technology, May 1991. (University Microfilms PUB 92-08460)
3. Aamodt, A. (1993): Explanation-driven retrieval, reuse, and learning of cases, In EWCBR-93: First European Workshop on Case-Based Reasoning. University of Kaiserslautern SEKI Report SR-93-12 (SFB 314) (Kaiserslautern, Germany, 1993) 279-284.
4. Althoff, K.D (1989): Knowledge acquisition in the domain of CNC machine centers; the MOLTKE approach. In: J. Boose, B. Gaines and J.-G. Ganascia (eds.): EKAW-89; Third European Workshop on Knowledge-Based Systems, Paris, July 1989, 180-195.
5. Althoff, K.-D. (1992): Machine learning and knowledge acquisition in a computational architecture for fault diagnosis in engineering systems. Proceedings of the ML-92 Workshop on Computational Architectures for Machine Learning and Knowledge Acquisition. Aberdeen, Scotland, July 1992.
6. Anderson, J.R. (1983): The architecture of cognition. Harvard University Press, Cambridge.
7. Aha, D., Kibler, D. and Albert, M.K. (1991): Instance-Based Learning Algorithms, Machine Learning, 6(1).
8. Allemagn, D. (1993): Review of EWCBR’93: 1st European Workshop on Case-Based Reasoning, AlCommunica-tions 7(2), in press.
9. Bareiss, R. (1989): Exemplar-based knowledge acquisition: A unified approach to concept representation, classification, and learning. Boston, Academic Press.
10. Ashley, K. (1991): Modeling legal arguments: Reasoning with cases and hypotheticals. MIT Press, Bradford Books, Cambridge.
11. Bareiss, R. (1988): PROTOS; a unified approach to concept representation, classification and learning. Ph.D. Dissertation, University of Texas at Austin, Dept, of Computer Sciences, Technical Report AI88-83.
12. Branting, K. (1991): Exploiting the complementarity of rules and precedents with reciprocity and fairness. In: Proceedings from the Case-Based Reasoning Workshop 1991, Washington DC, May 1991. Sponsored by DARPA. Morgan Kaufmann, 39-50.
13. Brown, B. and Lewis, L. (1991): A case-based reasoning solution to the problem of redundant resolutions of nonconformances in large scale manufacturing. In: R. Smith, C. Scott (eds.): Innovative Applications for Artificial Intelligence 3, MIT Press.
14. Burstein, M.H. (1989): Analogy vs. CBR; The purpose of mapping. Proceedings from the Case-Based Reasoning Workshop, Pensacola Beach, Florida, May-June 1989. Sponsored by DARPA. Morgan Kaufmann, 133-136.
15. Bomer, K. (1993): Structural similarity as guidance in case-based design. In: First European Workshop on Case-based Reasoning, Posters and Presentations, 1-5 November 1993. Vol. I. University of Kaiserslautern, 14-19.
16. Carbonell, J. (1986): Derivational analogy; A theory of reconstructive problem solving and expertise acquisition. In: R.S. Michalski, J.G. Carbonell, T.M. Mitchell (eds.): Machine Learning - An Artificial Intelligence Approach, Vol.II, Morgan Kaufmann, 371-392.
17. Cunningham, P. and Slattery, S. (1993): Knowledge engineering requirements in derivational analogy. In: First European Workshop on Case-based Reasoning, Posters and Presentations, 1-5 November 1993. Vol. I. University of Kaiserslautern, 108-113.
18. Proceedings from the Case-Based Reasoning Workshop, Pensacola Beach, Florida, May-June 1989. Sponsored by DARPA. Morgan Kaufmann, 1989.
19. Proceedings from the Case-Based Reasoning Workshop, Washington D.C., May 8-10, 1991. Sponsored by DARPA. Morgan Kaufmann, 1989.
20. First European Workshop on Case-based Reasoning, Posters and Presentations, 1-5 November 1993. Vol. I-II. University of Kaiserslautern.
21. The FABEL Consortium (1993): Survey of FABEL. FABEL Report No. 2, GMD, Sankt Augustin.
22. Gentner, D. (1983): Structure mapping - a theoretical framework for analogy. Cognitive Science, 7, 155-170.
23. Hall, R.P. (1989): Computational approaches to analogical reasoning; A comparative analysis. Artificial Intelligence, 39(1), 39-120.
24. Hammond, K.J. (1989): Case-based planning. Academic Press.
25. Harmon, P. (1992): Case-based reasoning III, Intelligent Software Strategies, VIII (1).
26. Hennessy, D. and Hinkle, D. (1992): Applying case-based reasoning to autoclave loading. IEEE Expert 7(5), 21-26.
27. Hinrichs, T.R. (1992): Problem solving in open worlds. Lawrence Erlbaum Associates.
28. IEEE Expert (1992): 7(5), Special issue on case-based reasoning. October 1992.
29. Keane, M. (1988): Where’s the Beef? The Absence of Pragmatic Factors in Pragmatic Theories of Analogy. In: Proc. ECAI-88, 327-332.
30. Kedar-Cabelli, S. (1988): Analogy - from a unified perspective. In: D.H. Helman (ed.), Analogical reasoning. Kluwer Academic, 65-103.
31. Kibler, D. and Aha, D. (1987): Learning representative exemplars of concepts; An initial study. Proceedings of the Fourth International Workshop on Machine Learning, UC-Irvine, 24-29.
32. Kitano, H. (1993): Challenges for massive parallelism. IJCAI-93, Proceedings of the Thirteenth International Conference on Artificial Intelligence, Chambéry, France, 1993. Morgan Kaufman, 813-834.
33. Kolodner, J. (1983a): Maintaining organization in a dynamic long-term memory. Cognitive Science, 1, 243-280.
34. Kolodner, J. (1983b): Reconstructive memory, a computer model. Cognitive Science, 7, 281-328.
35. Kolodner, J. (1988): Retrieving events from case memory: A parallel implementation. In: Proceedings from the Case-based Reasoning Workshop, DARPA, Clearwater Beach, 233-249.
36. Kolodner, J. (1992): An introduction to case-based reasoning. Artificial Intelligence Review 6(1), 3-34.
37. Kolodner, J. (1993): Case-based reasoning. Morgan Kaufmann.
38. Koton, P. (1989): Using experience in learning and problem solving. Massachusetts Institute of Technology, Laboratory of Computer Science (Ph.D. diss, October 1988). MIT/LCS/TR-441.
39. López, B. and Plaza, E. (1990): Case-based learning of strategic knowledge. Centre d’Estudis Avan$ats de Blanes, CSIC, Report de Recerca GRIAL 90/14. Blanes, Spain, (published in Y. Kodratoff (Ed.) Machine Learning-EWSML-91, 398-411. Lecture Notes in Computer Science, Springer Verlag).
40. López, B. and Plaza, E. (1993): Case-based planning for medical diagnosis, In: J. Komorowski, Z.W. Ras (Eds.) Methodologies for Intelligent Systems: 7th International Symposium, ISMIS ‘93, 96-105. Lecture Notes in Artificial Intelligence 689, Springer Verlag.
41. Manago, M., Althoff, K.-D. and Traphóner, R. (1993): Induction and reasoning from cases. In: ECML - European Conference on Machine Learning, Workshop on Intelligent Learning Architectures. Vienna.
42. Michalski, R. and Tecuci, G. (1992): Proc. Multistrategy Learning Workshop. George Mason University.
43. Nordbo, I., Skalle, P., Sveen, J., Aakvik, G., and Aamodt, A. (1992): Reuse of experience in drilling - Phase 1 Report. SINTEF DELAB and NTH, Div. of Petroleum Engineering. STF 40 RA92050 and IPT 12/92/PS/JS. Trondheim.
44. Oehlmann, R. (1992): Learning causal models by self-questioning and experimentation. AAAI-92 Workshop on Communicating Sientific and Technical Knowledge. American Association of Artificial Intelligence.
45. O’Hara, S. and Indurkhya, B. (1992): Incorporating (re)-interpretation in case-based reasoning. In: First European Workshop on Case-based Reasoning, Posters and Presentations, 1-5 November 1993. Vol. I. University of Kaiserslautern, 154-159.
46. Plaza, E. and López de Mántaras, R. (1990): A case-based apprentice that learns from fuzzy examples. In: Z. Ras, M. Zemankova and M.L. Emrich (Eds.) Methodologies for Intelligent System 5, 420-427. North Holland.
47. Plaza, E. and Arcos J.L. (1993):, Reflection and Analogy in Memory-based Learning, Proc. Multistrategy Learning Workshop, 42-49.
48. Porter, B. and Bareiss, R. (1986): PROTOS: An experiment in knowledge acquisition for heuristic classification tasks. In: Proceedings of the First International Meeting on Advances in Learning (IMAL), Les Arcs, France, 159-174.
49. Porter, B., Bareiss, R. and Holte, R. (1990): Concept learning and heuristic classification in weak theory domains. Artificial Intelligence, 45(1/2), 229-263.
50. Richter, A.M. and Weiss, S. (1991): Similarity, uncertainty and case-based reasoning in PATDEX. In: R.S. Boyer (ed.): Automated reasoning, essays in honour of Woody Bledsoe. Kluwer, 249-265.
51. Riesbeck, C. and Schank, R. (1989): Inside case-based reasoning. Lawrence Erlbaum.
52. Rissland, E. (1983): Examples in legal reasoning: Legal hypothetical. In: Proceedings of the Eighth International Joint Conference on Artificial Intelligence, IJCAI, Karlsruhe.
53. Ross, B.H. (1989): Some psychological results on case-based reasoning. Case-Based Reasoning Workshop, DAR-PA 1989. Pensacola Beach. Morgan Kaufmann, 144-147.
54. Schank, R. (1982): Dynamic memory; a theory of reminding and learning in computers and people. Cambridge University Press.
55. Schank, R. and Leake, D. (1989): Creativity and learning in a case-based explainer. Artificial Intelligence, 40(1-3), 353-385.
56. Schult, T. (1992): Werzeuge fur fallbaseierte systeme. Künstliche Intelligenz 3.
57. Sharma, S. and Sleeman, D. (1988): REFINER; a case-based differential diagnosis aide for knowledge acquisition and knowledge refinement. In: EWSL 88; Proceedings of the Third European Working Session on Learning, Pitman, 201-210.
58. Simoudis, E. (1992): Using case-based reasoning for customer techical support. IEEE Expert 7(5), 7-13.
59. Simpson, R.L. (1985): A computer model of case-based reasoning in problem solving: An investigation in the domain of dispute mediation. Technical Report GIT-ICS-85/18, Georgia Institute of Technology.
60. Skalak, C.B. and Rissland, E. (1992): Arguments and cases: An inevitable twining. Artificial Intelligence and Law, An International Journal 1(1), 3-48.
61. Slade, S. (1991): Case-based reasoning: A research paradigm. AI Magazine 42-55.
62. Smith, E. and Medin, D. (1981): Categories and concepts. Harvard University Press.
63. Stanfill, C. and Waltz, D. (1988): The memory based reasoning paradigm. In: Case based reasoning. Proceedings from a workshop, Clearwater Beach, Florida. Morgan Kaufmann Publ., 414-424.
64. Steels, L. (1990): Components of expertise, AI Magazine, 11(2), 29-49.
65. Steels, L. (1993): The componential framework and its role in reusability, In: J.-M. David, J.-P. Krivine and R. Simmons (eds.), Second generation expert systems, Spinger, 273-298.
66. Strube, G. and Janetzko, D. (1990): Episodishes Wissen und Fallbasierte Schliessen: Aufgabe fur die Wissen-dsdiagnostik und die Wissenspsychologie. Schweizerische Zeitschrift fur Psychologie 49, 211-221.
67. Strube, G. (1991): The role of cognititve science in knowledge engineering, In: F. Schmalhofer and G. Strube (eds.), Contemporary knowledge engineering and cognition: First joint workshop, proceedings, Springer, 161-174.
68. Sycara, K. (1988): Using case-based reasoning for plan adaptation and repair. Proceedings Case-Based Reasoning Workshop, DARPA. Clearwater Beach, Florida. Morgan Kaufmann, 425-434.
69. Tulving, E. (1977): Episodic and semantic memory. In: E. Tulving and W. Donaldson: Organization of memory, Academic Press, 381-403.
70. Veloso, M.M. and Carbonell, J. (1993): Derivational analogy in PRODIGY. In: Machine Learning 10(3), 249-278.
71. Venkatamaran, S., Krishnan, R. and Rao, K.K. (1993): A rule-rule-case based system for image analysis. In: First European Workshop on Case-based Reasoning, Posters and Presentations, 1-5 November 1993. Vol. II. University of Kaiserslautern, 410-415.
72. Wittgenstein, L. (1953): Philosophical investigations. Blackwell, 31-34.
73. Van de Velde, W. (1993): Issues in knowledge level modelling, In: J.-M. David, J.-P. Krivine and R. Simmons (eds.), Second generation expert systems, Springer Verlag, 211-231.
74. Schmalhofer, F. and Thoben, J. (1992): The model-based construction of a case-oriented expert system, AI Communications 5(1), 3-18.
75. Rouse, W.B. and Hurt, R.M. (1982): Human problem solving in fault diagnosis tasks, Georgia Institute of Technology, Center for Man-Machine Systems Research, Research Report no 82-3.