Differential adaptation: An operational approach to adaptation for solving numerical problems with CBR

International audienceCase-based reasoning relies on four main steps: retrieval, adaptation, revision and retention. This article focuses on the adaptation step; we propose differential adaptation as an operational formalization of adaptation for numerical problems. The solution to a target problem is designed on the basis of relations existing between a source case (problem and solution) and a target case. Differential adaptation relies on the metaphor of differential calculus where small variations on variable values are related to variations of function values. Accordingly, variations between problems correspond to variations between variable values and variations between solutions to variations between function values. Operators inspired from differential calculus are able to manipulate the variations and to support the whole adaptation process. Differential adaptation is operational and provides generic operators that can be reused for different real-world numerical situations

Improvement of online adaptation knowledge acquisition and reuse in case-based reasoning: Application to process engineering design

Despite various publications in the area during the last few years, the adaptation step is still a crucial phase for a relevant and reasonable Case Based Reasoning system. Furthermore, the online acquisition of the new adaptation knowledge is of particular interest as it enables the progressive improvement of the system while reducing the knowledge engineering effort without constraints for the expert. Therefore this paper presents a new interactive method for adaptation knowledge elicitation, acquisition and reuse, thanks to a modification of the traditional CBR cycle. Moreover to improve adaptation knowledge reuse, a test procedure is also implemented to help the user in the adaptation step and its diagnosis during adaptation failure. A study on the quality and usefulness of the new knowledge acquired is also driven. As our Knowledge Based Systems (KBS) is more focused on preliminary design, and more particularly in the field of process engineering, we need to unify in the same method two types of knowledge: contextual and general. To realize this, this article proposes the integration of the Constraint Satisfaction Problem (based on general knowledge) approach into the Case Based Reasoning (based on contextual knowledge) process to improve the case representation and the adaptation of past experiences. To highlight its capability, the proposed approach is illustrated through a case study dedicated to the design of an industrial mixing device

Development of a windows based computer-aided die design system for die casting

Master'sMASTER OF ENGINEERIN

Re-design of compositional systems

Treur, J. [Promotor]Brazier, F.M.T. [Copromotor