3.3. Case-Based Reasoning (CBR) Knowledge Component 3: Acquiring Data and Knowledge 3.3. Case-Based Reasoning (CBR) 2nd Edition Ian F. C. Smith EPFL, Switzerland

Module Information Novice Intended audience Key words Case-based reasoning, information retrieval, adaptation, case storage Author Ian F.C. Smith, EPFL, Switzerland 2

What there is to learn At the end of this module, there will be answers to the following questions: Why use cases? How can engineers ensure that good results are obtained? What are the long-term challenges? 3

Steps in Case-Based Reasoning Outline Introduction Steps in Case-Based Reasoning CBR Cycle CBR in Everyday Life

Principle Case-based reasoning (CBR) involves finding solutions to new tasks by reusing good solutions to old tasks. CBR systems have many advantages over other types of computer systems for decision support. Some of them are given in the following slides.

Advantages of CBR The process of storing cases often involves transformations that are computationally less expensive than those necessary with other representations. A good case is often an easy shortcut in the search for good solutions. The closed-world assumption associated with abductive tasks (Module 1.3) is explicitly related to the number of available cases.

Advantages (cont'd.) When only small changes are made to the old case, intrinsic advantages of the old case are transferred to the new task. Cases are often the best way to represent knowledge, especially when the available models are unreliable. The capability of the system can be enhanced by simply adding a case.

Advantages (cont'd.) Large case-based reasoning systems are currently used for diagnosis, maintenance, planning and customer support. There is much potential in civil engineering.

Steps in Case-Based Reasoning Outline Introduction Steps in Case-Based Reasoning CBR Cycle CBR in Everyday Life

Five Steps There are five main steps in the development and use of a CBR system. Representation Retrieval Adaptation Storage Maintenance

Step 1: Representation This step involves decisions related to how the case is stored in the computer. For example, if cases are to be stored in a relational database, appropriate attributes have to be selected. This is an important step since it can greatly influence the quality of support provided. One has to know clearly for what purpose the cases are intended before finalizing the representation.

Step 1: Representation (cont'd.) Characteristics of both task and solution must be represented. Task characteristics are used for case retrieval (Step 2) and solution characteristics are used for case adaptation (Step 3). Case = Task characteristics Solution characteristics +

Step 2: Retrieval This step involves the selection of a case (or cases) that have task characteristics which are similar to the new task. Here, the challenge involves defining what the word “similar” means. Hundreds of similarity metrics exist. The most common employ “nearest neighbor” methods.

Steps 2: Retrieval (cont'd.) Below is a simple example of a nearest neighbor method for numerical attributes. For a simple nearest neighbor calculation: For each task attribute, define a maximum value for the difference, Max.diff. This value sets the limit for similarity. Beyond this value, two attribute values are not similar.

Steps 2: Retrieval (cont'd.) Define weight factors wf using a scale that describes the relative importance of each task attribute. An iterative loop begins here: For the given case, for each task attribute, calculate the difference (absolute value) between the value for the attribute in the case and in the new task. Divide this difference by Max.diff. Values greater than 1 are set to 1. This result is called Distance.

Steps 2: Retrieval (cont'd.) Similarity = 1-Distance Evaluate the similarity variable for each task attribute Similarity = 1-Distance Calculate a weighted overall similarity measure between two cases [0…1] and return to step 3.

Steps 2: Retrieval (cont'd.) Report all cases having values for overall similarity that are above a pre-set level. If possible, it is always preferable to report more than one case. Engineers often want computers to give them choices, not answers, see Module 1.3. At this point, users may choose to ignore certain cases according to considerations that are not represented in the task attributes.

Steps 3: Adaptation The adaptation stage is the most difficult to implement on a computer. Here, the solution attributes of the retrieved case(s) are modified to suit the new task. This is seldom automated. User interaction is often essential in order to bring in the domain knowledge necessary for creating a useful solution.

Steps 3: Adaptation (cont'd.) While this stage is poorly supported in many commercial systems, it is the crucial stage of case-based reasoning. Without this stage, case-based reasoning would be no more than an exercise in information retrieval.

Steps 4: Storage The storage stage involves storing the newly found solution in the case base for future use. If the solution is within the scope of solutions that were envisaged when case attributes were defined, this stage is straightforward.

Steps 5: Maintenance The maintenance stage involves elimination of cases that are no longer relevant to the tasks that will come in the future. This stage may also include the task of ensuring that the cases uniformly cover the entire range of possible attribute values.

Steps in Case-Based Reasoning Outline Introduction Steps in Case-Based Reasoning CBR Cycle CBR in Everyday Life

The CBR Cycle Initial Cases Storage Solution Data Base Adaptation Maintenance Retrieval New Task

Steps in Case-Based Reasoning Outline Introduction Steps in Case-Based Reasoning CBR Cycle CBR in Everyday Life

CBR in Everyday Life The concept of CBR is used in other fields where decisions are required in “open worlds”. Medicine Doctors remember previous medical cases, especially for rare symptoms Law Case histories are always consulted Judgments often depend on precedents Management Learning through study of previous cases

Suitability of CBR Well suited tasks Classification Diagnosis Prediction Control Harder for CBR Synthesis of systems Engineering design Planning of complex projects

Review Quiz List the process steps for all CBR methods. What are characteristics that indicate that a CBR approach may be suitable? What is the end criterion for retrieval?

Answers to Review Quiz List the process steps for all CBR methods. Retrieve the most similar case(s) comparing the present case to the library of past cases Select a retrieved case to solve the current task Adapt the old case to make a new solution Retain the new solution as a new case Maintain the case base

Answers to Review Quiz What are characteristics that indicate that a CBR approach may be suitable? Records of previously solved problems exist Remembering previous experience is useful Cases can be represented and stored without excessive use of resources Adaptation of cases is feasible Maintenance that ensures complete and uniform coverage is possible

Answers to Review Quiz What is the end criterion for retrieval? Retrieval is complete when the best matching case is found. Subtasks involve: identifying a set of relevant problem descriptors matching the case and returning a set of sufficiently similar cases (given a similarity criterion) selecting the best case from the set of cases returned

Summary CBR involves finding solutions to new tasks by reusing good solutions to old tasks. The capability of a system can be increased by simply adding a case. There are 5 stages in the CBR methodology: Representation Retrieval Adaptation Storage Maintenance

Answers to initial questions Why use cases? Cases provide good answers to previous challenges. They are shortcuts to solutions; they may contain valuable implicit knowledge; they are useful when no domain models exist; adding knowledge involves just adding a case. How can engineers ensure that good results are obtained? Cases need to uniformly cover all possible applications What are the long-term challenges? Maintenance: dropping irrelevant cases and ensuring uniform coverage.

Further Reading J. Kolodner. Case-Based Reasoning. Morgan Kaufmann Publishers, San Mateo, CA, 1993 Raphael, B. and Smith, I.F.C. Fundamentals of Computer-Aided Engineering, Wiley, 2003 Case-Based Reasoning on the Web, University of Kaiserslautern, http://www.cbr-web.org