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Methods

CBR can be divided into different methods. Aamodt and Plaza [4] describe five different methods, which can be discriminated by their dependency on a large number of cases, domain knowledge and whether they are able to modify solutions to suit new problems.

Exemplar-based reasoning - CBR is seen as a task of classifying a new case into a given set of classes which consists of previously experienced (prototypical) cases. The classes represent the set of possible solutions, and it is therefore not possible to modify a solution. This method is useful for weak theory domains.
Instance-based reasoning - A highly syntactic specialization of Exemplar-based reasoning without domain knowledge.
Memory-based reasoning - The collection of cases is seen as a large memory, and reasoning consists of accessing and searching the memory.
Case-based reasoning - Typical CBR systems have some richness of information, and a certain complexity in its internal organization. It is able to modify, or adapt a retrieved solution when it is used to solve a problem with another context than described in the case.
Analogy-based reasoning - Methods that are able to solve problems by using experience from a different domain.

The first three methods typically require more recorded cases than the latter two, because they lack domain knowledge.

**Figure 2.1:** A Knowledge Rich CBR System.
$\begin{figure} \begin{center} \scalebox {0.3}{\includegraphics{cbrknow.eps}} \end{center}\end{figure}$

A CBR-method which relies heavily on domain knowledge is called knowledge rich . This is illustrated in Fig 2.1, where the crosses indicate cases, and the circle the area of new cases that the system is able to handle with the domain knowledge and the case. By a case in these systems, we mean ``a user experience''.

**Figure 2.2:** A Knowledge Poor CBR System.
$\begin{figure} \begin{center} \scalebox {0.3}{\includegraphics{cbrdata.eps}} \end{center}\end{figure}$

If the system relies heavily on cases, it is called knowledge poor . This is illustrated in Fig 2.1. By cases we here use a more modest definition, ``a data record''. Some existing systems are placed according to their dependency on data and knowledge in Fig 2.1. The systems that will be further discussed here are KATE and Creek.

**Figure 2.3:** Dependency on Knowledge and Data for Some Existing Systems.
$\begin{figure} \begin{center} \scalebox {0.3}{\includegraphics{cbrsyst.eps}} \end{center}\end{figure}$

Next: Decomposition of CBR Up: Case-Based Reasoning Previous: Case-Based Reasoning

Torgeir Dingsoyr
2/26/1998