Experimental study of a similarity metric for retrieving pieces from structured plan cases: its role in the originality of plan case solutions

This paper describes a quantitative similarity metric and its contribution to achieve original plan solutions. This similarity metric is used by an iterative process of piece retrieval from structured plan cases. Within our approach plan cases are tree-like networks of pieces (goals and actions). These case pieces are ill-related each other by links (explanations). These links may be classified as hierarchical or temporal, antecedent or consequent, and explicit or implicit. Besides links, each case piece has also information about its properties (the attributes-value pairs), its hierarchical and temporal position in the case (the address), and about its constraints in the relationship with others (the constraints). The similarity metric computes a similarity value between two case pieces taking into account similarities between these case piece’s information types. Each time a problem is proposed, different weights are given to some of those similarities, with the aim of solving it with an original solution. This similarity metric is used by the system INSPIRER (ImagiNation taking as Source Past and Imperfectly REalated Reasonings). We illustrate the role of the similarity metric in the creativity of solutions, focusing specially their originality, with the presentation of the experimental results obtained in the musical composition domain, which is considered by us as a planning domain

Knowledge maintenance in myCBR

CBR systems, being knowledge based systems, process knowledge. Due to changes in the environment a CBR system’s knowledge model can become outdated, thus creating a need for constant maintenance of said knowledge model. In this paper, we describe an implementation of (semi-)automatic knowledge maintenance of two of the four knowledge containers of CBR systems, specifically case base maintenance and maintenance of similarity measures within the CBR system development SDK myCBR. We describe our approach to create, elicit and manage quality measures that are used to trigger maintenance actions if the quality measures fall below defined thresholds, indicating a declining efficiency/accuracy of a case base or particular similarity measure. We further detail on the implementation of our approach into myCBR Workbench to enable a knowledge engineer to incorporate the notion of maintenance already at the design stage of a CBR system. The approach relies on the notion of maintenance attributes to be able to measure the quality of case bases and similarity measures. Initial experiments using the newly introduced quality measurement attributes indicate that our approach is promising

Auto-incrémentation d'une base dysfonctionnelle de cas pour un système d'aide au diagnostic et à la réparation.

International audienceLe raisonnement à partir de cas est une méthode d'intelligence artificielle largement utilisée dans la résolution de problème de diagnostic technique. Après avoir mis en place un système de diagnostic et de réparation dédié à un système de transfert de palette, nous nous sommes intéressés à la maintenance de ce système et tout particulièrement à l'optimisation de la base de cas qui est au coeur du système et à sa remise à jour. Nous proposons dans cet article dans un premier temps d'optimiser la base de cas d'un système de raisonnement à partir de cas dédié au diagnostic de pannes et dans un deuxième temps d'enrichir la connaissance de ce système en rejoutant des cas de diagnostic non recensés d'une manière dynamique, sans altérer la structure de la base de cas mise en place. Ces 2 propositions ont été mises en place sur une plateforme de e-maintenance

Two functions of analogical reasoning in design. A cognitive-psychology approach

International audienceOn the basis of data collected in three empirical studies conducted on industrial designers, this paper identifies two different types of "spontaneous" use of analogy in design. Focus is on the first "stages" of analogical reasoning, i.e. construction of a target representation, and search and retrieval of a source. At the action-execution level, analogies are used in order to solve the current design problem; at the action-management level, in order to make the action-execution process cognitively more economical. Differences between the uses concern their dependence on the routine -character of the task, the distance between target and source, and their link with creativity and reuse (or case-based reasoning)

Sistemas híbridos neuro-simbólicos: una revisión.

Este artículo presenta una revisión general de los sistemas híbridos neuro-simbólicos de inteligencia artificial, centrándose en aquellos compuestos por Sistemas de Razonamiento Basados en Casos (CBR) y Redes Neuronales Artificiales (ANN). Un sistema híbrido de inteligencia artificial está formado por la integración de varios subsistemas inteligentes, los cuales colaboran entre sí y se influyen mutuamente. En este artículo se muestran varias clasificaciones de estos sistemas, prestando especial atención a las características distintivas de cada uno de los subsistemas que componen los modelos híbridos

Application of the Revision Theory to Adaptation in Case-Based Reasoning: the Conservative Adaptation

International audienceCase-based reasoning aims at solving a problem by the adaptation of the solution of an already solved problem that has been retrieved in a case base. This paper defines an approach to adaptation called conservative adaptation; it consists in keeping as much as possible from the solution to be adapted, while being consistent with the domain knowledge. This idea can be related to the theory of revision: the revision of an old knowledge base by a new one consists in making a minimal change on the former, while being consistent with the latter. This leads to a formalization of conservative adaptation based on a revision operator in propositional logic. Then, this theory of conservative adaptation is confronted to an application of case-based decision support to oncology: a problem of this application is the description of a patient ill with breast cancer, and a solution, the therapeutic recommendation for this patient. Examples of adaptations that have actually been performed by experts and that can be captured by conservative adaptation are presented. These examples show a way of adapting contraindicated treatment recommendations and treatment recommendations that cannot be applied

A methodology to conceive a case based system of industrial diagnosis.

International audienceThe objective of this paper is to address the diagnosis knowledge-oriented system in terms of artificial intelligence, particular by the Case-Based Reasoning (CBR) approach. Indeed, the use of CBR, which is an approach to problem solving and learning, in diagnosis goes back to a long time with the appearance of diagnostic support systems based on CBR. A diagnostic system by CBR implements an expertise-base composed of past experiences through which the origins of failure and the maintenance strategy are given according to a description of a specific situation of diagnostic. A study is made on the different diagnostic systems based on CBR. This study showed that there was no common methodology for building a CBR system. This design depends primarily on the case representation and knowledge models of the domain application. Consequently, this paper proposes a general design approach of a diagnostic system based on the CBR approach