Case-Based
Reasoning
(a
subtopic of Reasoning)
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"At the highest level of generality, a general CBR cycle may be described by the following four processes:
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CBR
in Context: The Present and Future. By David B. Leake. This chapter from
Case-Based 
Reasoning:
Experiences, Lesons, and Future Directions, David B. Leake, editor (AAAI
Press / MIT Press, 1996) is available online and "provides an introduction to case-based
reasoning, discusses motivations
for CBR, and describes the central steps in the CBR process. It examines
the relationship of CBR to other approaches, and discusses major research
areas, open issues, and promising opportunities for CBR. It surveys and
relates numerous approaches within CBR and provides more than 150 references
to international CBR research." [Here's
an illustration from this chapter portraying the dynamics of CBR.]
- Resources available from Professor Leake's pages at Indiana University include:
- Overview of Case-Based Reasoning (CBR) at Indiana University: "Case-based problem-solving solves problems by retrieving and applying solutions to previous problems. CBR research at Indiana investigates CBR for design support, planning and explanation. Our projects focus especially on issues in case-base maintenance, the use of introspective reasoning to refine indexing and adaptation, integration of CBR with other information tools in a larger task context, case-based knowledge management, and case-based components for scientific computing."
- Collection of selected publications that are available online.
- Links to past projects such as the SWALE project which "explores case-based reasoning (CBR) as a basis for creativity."
- See their collection of CBR Projects that includes fraud detection, information retireval, and more.
Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. By A. Aamodt and E. Plaza. (1994) Artificial Intelligence Communications, IOS Press, Vol. 7:1, pp. 39 - 59. Very thorough and very clearly written. "A very important feature of case-based reasoning is its coupling to learning. The driving force behind case-based methods has to a large extent come from the machine learning community, and case-based reasoning is also regarded a subfield of machine learning."
- for more info about Machine Learning, click here.
Some examples of CBR at work from the Sixteenth Innovative Applications of Artificial Intelligence Conference (IAAI-04):
- Deployed Application Papers:
- Tenth Anniversary of the Plastics Color Formulation Tool. By William Cheetham. "Since 1994 GE Plastics has employed a case-based reasoning tool that determines color formulas which match requested colors. This tool, called FormTool, has saved GE millions of dollars in productivity and material (i.e. colorant) costs. The technology developed in FormTool has been used to create an on-line color selection tool for our customers called ColorXpress Select. A customer innovation center has been developed around the FormTool software."
- The General Motors Variation-Reduction Adviser: Deployment Issues for an AI Application. By Alexander P. Morgan, John A. Cafeo, Kurt Godden, Ronald M. Lesperance, Andrea M. Simon, Deborah L. McGuinness, and James L. Benedict. "The General Motors Variation-Reduction Adviser is a knowledge system built on case-based reasoning principles that is currently in use in a dozen General Motors Assembly Centers. This paper reviews the overall characteristics of the system and then focuses on various AI elements critical to support its deployment to a production system. A key AI enabler is ontology-guided search using domain-specific ontologies."
- Emerging Application Papers
- CaBMA: Case-Based Project Management Assistant. By Ke Xu and Héctor Muñoz-Avila. "We are going to present an implementation of an AI system, CaBMA, built on top of a commercial project management tool, MS Project. Project management is a business process for successfully delivering one-of-a kind products and services under real-world time and resource constraints. CaBMA (for: Case-Based Project Management Assistant) provides the following functionalities: (1) It captures cases from project plans. (2) It reuses captured cases to refine project plans and generate project plans from the scratch. (3) It maintains consistency of pieces of a project plan obtained by case reuse. (4) It refines the case base to cope with inconsistencies resulting from capturing cases over a period of time. CaBMA adds a knowledge layer on top of MS Project to assist the user with his project management tasks."
ALSO SEE: ANALOGY: "Analogy-based reasoning: This term is sometimes used, as a synonym to case-based reasoning, to describe the typical case-based approach... However, it is also often used to characterize methods that solve new problems based on past cases from a different domain, while typical case-based methods focus on indexing and matching strategies for single-domain cases." -A. Aamodt and E. Plaza
A Discourse on Law and Artificial Intelligence. By Michael Aikenhead (1996). 5 Law Technology Journal 1. "[T]he dichotomy between rule based systems and cased based reasoning systems in AI and law research reflects an underlying jurisprudential debate that has raged for the last century. ... Instead of implying that legal reasoning is primarily a process of deduction or a process of analogising the theory of law as discourse requires a richer view of the process of legal reasoning."
- Also see our Law page.
The Third International Conference on Case-Based Reasoning (ICCBR '99). By Klaus-Dieter Althoff, Ralph Bergmann, and Karl Branting. AI Magazine 22(1): 116-118 (Spring 2001). "Case-based reasoning (CBR) is a problem-solving paradigm that uses exemplars or previous solutions to solve new problems (Aamodt and Plaza 1994; Kolodner 1993). Three characteristics of CBR account for its growing popularity. First, CBR can reduce search. ... The second characteristic is that CBR permits problem solving even when the underlying domain theory is incomplete. ... Finally, CBR can facilitate knowledge acquisition. ... The conference began with an Industry Day, chaired by Brigitte BartschSporl (BSR Consulting Munich) and Wolfgang Wilke (tecinno GmbH, Kaiserslautern). The Industry Day presentations illustrated a number of successful commercial applications of CBR in the United States and Europe. ..."
Applying Case-Based Reasoning to Manufacturing. By David Hinkle and Christopher Toomey. AI Magazine 16(1): 65-73 (Spring 1995). "CLAVIER is a case-based reasoning (CBR) system that assists in determining efficient loads of composite material parts to be cured in an autoclave. CLAVIER's central purpose is to find the most appropriate groupings and configurations of parts (or loads) to maximize autoclave throughput yet ensure that parts are properly cured. CLAVIER uses CBR to match a list of parts that need to be cured against a library of previously successful loads and suggest the most appropriate next load. clavier also uses a heuristic scheduler to generate a sequence of loads that best meets production goals and satisfies operational constraints. The system is being used daily on the shop floor and has virtually eliminated the production of low-quality parts that must be scrapped, saving thousands of dollars each month. As one of the first fielded CBR systems, CLAVIER demonstrates that CBR is a practical technology that can be used successfully in domains where more traditional approaches are difficult to apply."
Case-Based Reasoning. By Dr. Bonnie Morris, West Virginia University. A succinct and understandable explanation.
A Distributed Case-Based Reasoning Application for Engineering Sales Support. By Ian Watson and Dan Gardingen. In Proceedings 16th International Joint Conference on Artificial Intelligence (IJCAI-99), Vol. 1: pp. 600-605. Morgan Kaufmann Publishers. This paper received the IJCAI-99 Distinguished Paper Award.
ai-cbr. [Note: Although this site is no longer being maintained, there's still plenty of basic information and leads to additional resources.] There's something for everyone at this site, such as a page about applied CBR, a page offering actual case bases you can download, a searchable bibliography, and even a virtual library.
- Start with a visit to the classroom where amongst the many wonderful materials, is the suggested introductory article Case-Based Reasoning: A Review, by Ian Watson & Farhi Marir.
- CBR research projects in areas such as design, estimating, planning, decision support, finance, and legal reasoning.
- CBR commercial applications
Automated Case Based Reasoning (CBR) at NRC-IIT, Canada's National Research Council's (NRC) Institute for Information Technology (IIT)
CBR Resources. From David W. Aha.
Case Based Reasoning in Cardiovascular Disease. "Learning diagnostic expertise from experience." A project from the Clinical Decision Making Group at the MIT Laboratory for Computer Science.
Case-Based Reasoning Group at the University of Massachusetts at Amherst, Department of Computer Science. "Current research projects include projects to investigate the use of multiple case representation and indexing schemes in precedent-based CBR, the effect of high level reasoning goals on supporting CBR tasks and vice versa in a mixed paradigm blackboard-based architecture, the use of CBR for generation of retrieval strategies in the context of information retrieval, and the automatic selection of parameters for dynamic scheduling problems."
Case-Based Reasoning Research Group at the University of Pittsburgh. Check out their projects, and don't miss their papers about Intelligent Tutoring, Textual Case-Based Reasoning, and Ethical Reasoning.
Case-Based Reasoning Resources. Maintained by David Leake.
International Conference on Case-Based Reasoning.
Bergmann, R., Althoff, K.-D., Breen, S., Göker, M., Manago, M., Traphöner, R., and Wess, S. 2003. Developing Industrial Case-Based Reasoning Applications The INRECA Methodology (2nd Edition). Lecture Notes in Artificial Intelligence, Vol. 1612. Springer - Buchreihe
Nagel, Rebecca Thompson. June/July 1998. HAL, Esq. - Will computers someday replace attorneys in the delivery of legal services? We profile one woman whose work with artificial intelligence could forecast the future of the profession. Law Office Computing (subscription req'd.). "A computer that can think like an attorney? Artificial intelligence in a real-life application? Science fiction, right? Well, a system like the one described above is not yet available...commercially. But it does exist in the laboratory of University of Massachusetts, Amherst professor Dr. Edwina Rissland. ... The key to these programs is case-based reasoning (CBR) -- a subsection of AI that uses examples and analogy, as opposed to rules or logic, to solve problems."