Case-based reasoning is a problem solving paradigm which emphasizes the reuse of stored cases to solve new similar problems [2]. The cases are composed by a problem description (in simple domains just a list at attribute, value pairs) and by the solution to the problem. CBR involves a number of techniques for indexing cases, retrieving them, possibly adapting the retrieved solution, and for man...

A surprisingly large number of research disciplines have contributed towards the development of knowledge on lazy problem solving which is characterized by its stor age of ground cases and its demand driven response to queries Case based reasoning CBR is an alternative increasingly popular approach for designing expert systems that implements this approach This paper lists pointers to some cont...

Good estimates of development effort play an important role in the successful management of larger software development projects. This paper compares the prediction accuracy of three CBR techniques to estimate the effort to develop Web hypermedia applications. Most comparative studies have used one CBR technique. We believe this may bias the results, as there are several CBR techniques that may...

Recent work within the CBR community has studied more systematic means of interrelating different types of domain knowledge, tasks, and methods for building and maintaining CBR systems. This paper reviews work from the knowledge acquisition community, targeted at methodologies and tools for analysis, modeling, and maintenance of knowledge components. It is argued that the knowledge level is the...

This paper presents a unifying framework to model casebased reasoning recommender systems (CBR-RSs). CBR-RSs have complex architectures and specialize the CBR problem solving methodology in a number of ways. The goal of the proposed framework is to illustrate both the common features of the various CBR-RSs as well as the points were these systems take different solutions. The proposed framework...

Case-Based Reasoning (CBR) can support hydraulic circuit design. Existing expert systems for hydraulic system design use production rules as its source of knowledge. However, this leads to problems of knowledge acquisition and knowledge base maintenance. This paper describes the application of CBR to hydraulic circuit design for production machines, which helps solving problems using past exper...

Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to similar problems that were solved in the past). It has enjoyed considerable success in a wide variety of problem solving tasks and domains. Following a brief overview of the tr...

Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to similar problems that were solved in the past). It has enjoyed considerable success in a wide variety of problem solving tasks and domains. Following a brief overview of the tr...

This paper brings together factor-based models of case-based reasoning (CBR) and the logical specification classifiers. Horty [8] has developed precedent into a theory precedential constraint. In this we combine binary-input classifier logic (BCL) to classifiers their explanations given by Liu & Lorini [13, 14] with Horty’s account CBR, since both CBR map sets features decisions or classifi...

Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to similar problems that were solved in the past). It has enjoyed considerable success in a wide variety of problem solving tasks and domains. Following a brief overview of the tr...