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This paper describes how is represented knowledge in the Intelligent Tutoring System (ITS) AMBRE-add. This ITS intend to teach methods and is based on didactical studies and cognitive psychology studies. The Case-Based Reasoning paradigm is used to help the learner to find himself problems classes, using problems he or she has already seen during the learning. We describe how is represented domain knowledge and pedagogic knowledge in this ITS, presenting the architecture of a knowledge based system that enable to give help to the learner, to diagnose his or her answers and to explain his or her mistakes., Dans cet article, nous décrivons comment sont représentées les connaissances dans l'Environnement Informatique pour l'Apprentissage Humain (EIAH) AMBRE-add. Cet EIAH, destiné à l'apprentissage d'une méthode de résolution de problèmes additifs, s'appuie sur des études en didactique des mathématiques et en psychologie cognitive. Il exploite le paradigme du raisonnement à partir de cas pour permettre à l'apprenant de mettre lui-même en évidence des classes de problèmes, en utilisant des problèmes qu'il a déjà rencontrés au cours de l'apprentissage. Nous décrivons comment sont représentées les connaissances du domaine et les connaissances pédagogiques dans cet EIAH, en présentant l'architecture du système à base de connaissances permettant d'assurer des fonctionnalités d'aide, de diagnostic des réponses de l'apprenant et d'explication de ses erreurs.

International audience; Most of the algorithms developed within the Constraint Satisfaction Problem (CSP) framework cannot be used as such to solve interactive decision support problems, like product configuration. Indeed, in such problems, the user is in charge of assigning values to variables. Global consistency maintaining is only one among several functionalities that should be offered by a CSP-based platform in order to help the user in her task; other important functionalities include providing explanations for some user's choices and ways to restore consistency. This paper presents an extension of the CSP framework in this direction. The key idea consists in considering and handling the user's choices as assumptions. From a theoretical point of view, the complexity issues of various computational tasks involved in interactive decision support problems are investigated. The results cohere with what is known when Boolean constraints are considered and show all the tasks intractable in the worst case. Since interactivity requires short response times, intractability must be circumvented some way. To this end, we present a new method for compiling configuration problems, that can be generalized to valued CSPs. Specifically, an automaton representing the set of solutions of the CSP is first computed off-line, then this data structure is exploited so as to ensure both consistency maintenance and computation of maximal consistent subsets of user's choices in an efficient way.

Acknowledgements go to Zhang Yuhua (ISTIC), Xiao Long (Beijing University), and Jin Bihui (DICCAS) The internationalization and the visibility of Chinese journals covered by the Institute for Scientific Information (ISI) are discussed. Attention is focused on physics and chemistry journals. For these journals the country of origin of published papers and their citation patterns are analysed. As an indicator of internationality we further consider the composition of their editorial boards. It is concluded that even those Chinese journals that are covered by ISI are still rather ‘local’ and suffer from a low visibility in the world. Yet we are optimistic about the future of Chinese science and its scientific journals. National Natural Science Foundation of China

In this paper, the members of the computer science laboratory of Le Mans (LIUM), in the AIED and microworld team, show the researches that have been undertaken under the direction or the impulsion of Martial Vivet. A first part of the text underlines the foundations of the scientific policy and describes the works of the team around three main strands : intelligent tutoring systems and pedagogical planning, microworlds design for vocational training, and, finally, learning situations modelling and open and distributed learning environments. A discussion about current research issues closes this overview., Dans ce texte, les membres du LIUM ayant travaillé dans l’équipe EIAO présentent les recherches conduites sous la direction de Martial Vivet ou impulsées par lui. Une première partie développe les fondements de la politique scientifique suivie et décrit les travaux de l’équipe en les regroupant autour de trois axes principaux : les tuteurs intelligents et la planification pédagogique, la conception de micromondes pour la formation professionnelle et, enfin, la modélisation des situations d’apprentissage et les environnements d’apprentissage ouverts et distribués. Une discussion autour des problématiques de recherche actuelles dans le domaine termine ce tour d’horizon., Bruillard Eric, Delozanne Elisabeth, Leroux Pascal, Delannoy Paul, Dubourg Xavier, Jacoboni Pierre, Lehuen Jérôme, Luzzati Daniel, Teutsch Philippe. Quinze ans de recherche informatique sur les sciences et techniques éducatives au LIUM. In: Sciences et techniques éducatives, volume 7 n°1, 2000. Education et informatique. Hommage à Martial Vivet. pp. 87-145.

Machine Learning (ML) is increasingly prominent in or- ganizations. While those algorithms can provide near perfect accuracy, their decision-making process remains opaque. In a context of accelerating regulation in Artificial Intelligence (AI) and deepening user awareness, explainability has become a priority notably in critical healthcare and financial environ- ments. The various frameworks developed often overlook their integration into operational applications as discovered with our industrial partner. In this paper, explainability in ML and its relevance to our industrial partner is presented. We then dis- cuss the main challenges to the integration of ex- plainability frameworks in production we have faced. Finally, we provide recommendations given those challenges.

In this paper we argue that transparency of machine learning algorithms, just as explanation, can be defined at different levels of abstraction. We criticize recent attempts to identify the explanation of black box algorithms with making their decisions (post-hoc) interpretable, focusing our discussion on counterfactual explanations. These approaches to explanation simplify the real nature of the black boxes and risk misleading the public about the normative features of a model. We propose a new form of algorithmic transparency, that consists in explaining algorithms as an intentional product, that serves a particular goal, or multiple goals (Daniel Dennet's design stance) in a given domain of applicability, and that provides a measure of the extent to which such a goal is achieved, and evidence about the way that measure has been reached. We call such idea of algorithmic transparency "design publicity." We argue that design publicity can be more easily linked with the justification of the use and of the design of the algorithm, and of each individual decision following from it. In comparison to post-hoc explanations of individual algorithmic decisions, design publicity meets a different demand (the demand for impersonal justification) of the explainee. Finally, we argue that when models that pursue justifiable goals (which may include fairness as avoidance of bias towards specific groups) to a justifiable degree are used consistently, the resulting decisions are all justified even if some of them are (unavoidably) based on incorrect predictions. For this argument, we rely on John Rawls's idea of procedural justice applied to algorithms conceived as institutions., Ethics and Information Technology, 23 (3), ISSN:1388-1957, ISSN:1572-8439