The underlying motivation for the authors’ research on constraint understanding is comparative constraint understanding. The same constraint can be expressed in different ways in different models, and a comparative constraint-understanding system would be able to assess the extent to which two models have equivalent constraint semantics. Understanding constraint semantics can be used to support...

This paper describes a case-based reasoning (CBR) approach that supports the design of azeotropic separation process structures. CBR finds the most similar existing separation processes and applies the knowledge of their concept for solving new problems. The method is applicable especially in the early phases of process design.

This paper focuses on problems where the reuse of old solutions seems appropriate but the conventional CBR methodology is not adequate because a complete description of the new problem is not available to trigger case retrieval. We describe an information theoretic technique that solves this problem by producing focused questions to fill out the case description. This use of information theoret...

A case-based reasoning system for determining what colorants to use for producing a specific color of plastic was created. The selection of colorants needs to take many factors into consideration. A technique that involved fuzzy logic was used to compare the quality of the color match for each factor. The system has been in use for two years at a growing number of GE Plastics sites and has show...

In this paper we will introduce a measure of saturation for unstructured texts of unknown domains. Therefore we will present the Textual Coverage Rate (TCR), a method to determine the IE coverage of unstructured texts using a given vocabulary. We advance efficiency while building vocabulary repositories tailored for given problems and ensure a certain quality of representation. Our approach, wh...

This paper explores a method to algorithmically distinguish case-specific facts from potentially reusable or adaptable elements of cases in a textual case-based reasoning (TCBR) system. In the legal domain, documents often contain casespecific facts mixed with case-neutral details of law, precedent, conclusions the attorneys reach by applying their interpretation of the law to the case facts, a...

Textual CBR applications deal with problems that have traditionally been addressed by the Information Retrieval community, namely the handling of textual documents. Since CBR is an AI technique, the questions arise as to what kind of knowledge may enhance the system, where this knowledge comes from, and how it contributes to the performance of such a system. We will address these questions in t...

This paper focuses on the problem of choosing the best match among a set of retrieved cases. The Select step is subtask of case retrieval that produces the case that suggests the solution for the input case. There are many different ways to accomplish this task and we propose an automatic means for it. Following the original motivation of paralleling the human similarity heuristic we argue that...

Creating AI for complex computer games requires a great deal of technical knowledge as well as engineering effort on the part of game developers. This paper focuses on techniques that enable end-users to create AI for games without requiring technical knowledge by using case-based reasoning techniques. AI creation for computer games typically involves two steps: a) generating a first version of...

Evaluation is an important issue for every scientific field and a necessity for an emerging software technology like case-based reasoning. This paper is a supplementation to the review of industrial case-based reasoning tools by K.-D. Althoff, E. Auriol, R. Barletta and M. Manago which describes the most detailed evaluation of commercial case-based reasoning tools currently available. The autho...