An Algorithm for Adaptation in Case-based Reasoning

Colloque avec actes et comité de lecture. internationale.International audienceThe adaptation process is an important and complex step of case-based reasoning (CBR) and is most of the time designed for a specific application. This article presents a domain-independent algorithm for adaptation in CBR. Cases are mapped to a set of numerical descriptors filled with values and local constraint intervals. The algorithm computes every target solution descriptor by combining a source solution, a matching expressed as intervals of variations and dependencies between the source problem and its solution. It determines for every target solution descriptor an interval of the admissible values. In this interval, actual values satisfying global constraints can be chosen. This generic approach to adaptation is operational and introduces general and domain-independent adaptation operators. Therefore, this study is a contribution to the design of a general algorithm for adaptation in CBR

Algorithm for Adapting Cases Represented in a Tractable Description Logic

Case-based reasoning (CBR) based on description logics (DLs) has gained a lot of attention lately. Adaptation is a basic task in the CBR inference that can be modeled as the knowledge base revision problem and solved in propositional logic. However, in DLs, it is still a challenge problem since existing revision operators only work well for strictly restricted DLs of the \emph{DL-Lite} family, and it is difficult to design a revision algorithm which is syntax-independent and fine-grained. In this paper, we present a new method for adaptation based on the DL $\mathcal{EL_{\bot}}$. Following the idea of adaptation as revision, we firstly extend the logical basis for describing cases from propositional logic to the DL $\mathcal{EL_{\bot}}$, and present a formalism for adaptation based on $\mathcal{EL_{\bot}}$. Then we present an adaptation algorithm for this formalism and demonstrate that our algorithm is syntax-independent and fine-grained. Our work provides a logical basis for adaptation in CBR systems where cases and domain knowledge are described by the tractable DL $\mathcal{EL_{\bot}}$.Comment: 21 pages. ICCBR 201

Adaptation-Guided retrieval for a diagnostic and repair help system dedicated to a pallets transfer.

International audienceIn this paper, we describe a CBR approach for failure diagnosis of a pallets transfer. Adaptation phase is the key problem of the case-based reasoning system conception. This paper is a contribution to fill this gap in the equipments diagnostic and repair help. Retrieval step guided by adaptation is proposed, as a result measures associated with an adaptation measure are proposed. These two measures will make it possible to select among the retrieved cases the most adaptable case. Then, an adaptation algorithm is proposed and will rely on a descriptors hierarchy, a context model as well as the dependences between problem and solution of the source cases. A feasibility study of the proposed algorithm is made on a real industrial diagnosis case. Three scenarios are treated in this study concerning various dependency relation values and belonging to the hierarchical classes of descriptors

An Algorithm for Adapting Cases Represented in an Expressive Description Logic

The original publication is available at www.springerlink.comInternational audienceThis paper presents an algorithm of adaptation for a case-based reasoning system with cases and domain knowledge represented in the expressive description logic ALC. The principle is to first pretend that the source case to be adapted solves the current target case. This may raise some contradictions with the specification of the target case and with the domain knowledge. The adaptation consists then in repairing these contradictions. This adaptation algorithm is based on an extension of the classical tableau method used for deductive inference in ALC

Reutilization of diagnostic cases by adaptation of knowledge models.

International audienceThis paper deals with design of knowledge oriented diagnostic system. Two challenges are addressed. The first one concerns the elicitation of expert practice and the proposition of a methodology for developing four knowledge containers of case based reasoning system. The second one concerns the proposition of a general adaptation phase to reuse case solving diagnostic problems in a different context. In most cases, adaptation methods are application-specific and the challenge in this work is to make a general adaptation method for the field of industrial diagnostics applications. This paper is a contribution to fill this gap in the field of fault diagnostic and repair assistance of equipment. The proposed adaptation algorithm relies on hierarchy descriptors, an implied context model and dependencies between problems and solutions of the source cases. In addition, one can note that the first retrieved case is not necessarily the most adaptable case, and to take into account this report, an adaptation-guided retrieval step based on a similarity measure associated with an adaptation measure is realized on the diagnostic problem. These two measures allow selecting the most adaptable case among the retrieved cases. The two retrieval and adaptation phases are applied on real industrial system called Supervised industrial system of Transfer of pallets (SISTRE)

Adapting propositional cases based on tableaux repairs using adaptation knowledge -- extended report

Adaptation is a step of case-based reasoning that aims at modifying a source case (representing a problem-solving episode) in order to solve a new problem, called the target case. An approach to adaptation consists in applying a belief revision operator that modifies minimally the source case so that it becomes consistent with the target case. Another approach consists in using domain-dependent adaptation rules. These two approaches can be combined: a revision operator parametrized by the adaptation rules is introduced and the corresponding revision-based adaptation uses the rules to modify the source case. This paper presents an algorithm for revision-based and rule-based adaptation based on tableaux repairs in propositional logic: when the conjunction of source and target cases is inconsistent, the tableaux method leads to a set of branches, each of them ending with clashes, and then, these clashes are repaired (thus modifying the source case), with the help of the adaptation rules. This algorithm has been implemented in the REVISOR/PLAK tool and some implementation issues are presented

Telemedicine framework using case-based reasoning with evidences

Telemedicine is the medical practice of information exchanged from one location to another through electronic communications to improve the delivery of health care services. This research article describes a telemedicine framework with knowledge engineering using taxonomic reasoning of ontology modeling and semantic similarity. In addition to being a precious support in the procedure of medical decision-making, this framework can be used to strengthen significant collaborations and traceability that are important for the development of official deployment of telemedicine applications. Adequate mechanisms for information management with traceability of the reasoning process are also essential in the fields of epidemiology and public health. In this paper we enrich the case-based reasoning process by taking into account former evidence-based knowledge. We use the regular four steps approach and implement an additional (iii) step: (i) establish diagnosis, (ii) retrieve treatment, (iii) apply evidence, (iv) adaptation, (v) retain. Each step is performed using tools from knowledge engineering and information processing (natural language processing, ontology, indexation, algorithm, etc.). The case representation is done by the taxonomy component of a medical ontology model. The proposed approach is illustrated with an example from the oncology domain. Medical ontology allows a good and efficient modeling of the patient and his treatment. We are pointing up the role of evidences and specialist's opinions in effectiveness and safety of care

Case Based Reasoning Support for Adaptive Finite Element Analysis - Mesh Selection for an Integrated System

An Adaptive Finite Element Analysis Integrated System supported through application of Case Based Reasoning (CBR) methodology is being proposed in this paper. The approach is fruitful for selection of an initial mesh from a library of solutions to initiate analysis process, as already tested optimal mesh will have lesser refinement iterations. The optimal mesh distribution, represented by object-oriented method, can be easily adapted to the topology of new problem in same domain. An integrated and universal structural analysis system models human reasoning by forming solutions through the retrieval and adaptation of successful strategies used in the past. Basic insight of two distinct subjects along with resolution of involved issues and integration strategy for development of an intelligent system is elaborated here. The research explains an algorithm for case retrieval and mesh generation procedures based on the principles of mapping method

Supporting Knitwear Design Using Case-Based Reasoning

Organised by: Cranfield UniversityKnitwear design is a creative activity that is hard to automate using the computer. The production of the associated knitting pattern, however, is repetitive, time-consuming and error-prone, calling for automation. Our objectives are two-fold: to facilitate the design and to ease the burden of calculations and checks in pattern production. We conduct a feasibility study for applying case-based reasoning in knitwear design: we describe appropriate methods and show how they can be implemented.Mori Seiki – The Machine Tool Compan