Utilisation d'une algèbre temporelle pour la représentation et l'adaptation de recettes de cuisine

National audienceNous traitons ici de la représentation du temps et du raisonnement temporel qualitatif dans la cadre du raisonnement à partir de cas. Nous nous appuyons pour cela sur l'exemple jeu d'une application culinaire, ayant pour but de générer des recettes opérationnelles. Les suites d'opérations sont représentées par des graphes où les arêtes sont des relations entre intervalles temporels. L'adaptation des recettes peut alors s'effectuer grâce à des techniques de résolution de contraintes. Nous décrivons quelques exemples où ces techniques peuvent être mises en jeu. Nous concluons en situant l'approche proposée par rapport aux travaux combinant RàPC et représentation du temps ou planification

AGREE: a feature attribution aggregation framework to address explainer disagreements with alignment metrics.

As deep learning models become increasingly complex, practitioners are relying more on post hoc explanation methods to understand the decisions of black-box learners. However, there is growing concern about the reliability of feature attribution explanations, which are key to explaining machine learning models. Studies have shown that some explainable artificial intelligence (XAI) methods are highly sensitive to noise and that explanations can vary significantly between techniques. As a result, practitioners often employ multiple methods to reach a consensus on the reliability of their models, which can lead to disagreements among explainers. Although some literature has formalised and reviewed this problem, few solutions have been proposed. In this paper, we propose a novel case-based approach to evaluating disagreement among explainers and advance AGREE-an explainer aggregation approach to resolving the disagreement problem based on explanation weights. Our approach addresses the problem of both local and global explainer disagreement by utilising information from the neighbourhood spaces of feature attribution vectors. We evaluate our approach against simpler feature overlap metrics by weighting the latent space of a k-NN predictor using consensus feature importance and observing the performance degradation. For local explanations in particular, our method captures a more precise estimate of disagreement than the baseline methods and is robust against high dimensionality. This can lead to increased trust in ML models, which is essential for their successful adoption in real-world applications

Man-Machine Collaboration to Acquire Cooking Adaptation Knowledge for the TAAABLE Case-Based Reasoning System

International audienceThis paper shows how humans and machines can better collaborate to acquire adaptation knowledge (AK) in the framework of a case-based reasoning (CBR) system whose knowledge is encoded in a semantic wiki. Automatic processes like the CBR reasoning process itself, or speci c tools for acquiring AK are integrated as wiki extensions. These tools and processes are combined on purpose to collect AK. Users are at the center of our approach, as they are in a classical wiki, but they will now bene t from automatic tools for helping them to feed the wiki. In particular, the CBR system, which is currently only a consumer for the knowledge encoded in the semantic wiki, will also be used for producing knowledge for the wiki. A use case in the domain of cooking is given to exemplify the man-machine collaboration

Actes du 17ème séminaire sur le raisonnement à partir de Cas, Paris (29--30 juin)

Actes du séminaire RàPC 2009

18ème Atelier "Raisonnement à Partir de Cas" RàPC 2010

National audienceLe raisonnement à partir de cas (RàPC) est un paradigme de résolution de problèmes s'appuyant sur la réutilisation d'expériences passées pour résoudre de nouveaux problèmes. Les applications du RàPC sont nombreuses et la recherche est particuli'erement active en France et dans le monde. Les rencontres annuelles de la communauté fran¸caise ont été organisées depuis 1992 par le groupe français de recherche en RàPC, sous la forme d'ateliers d'un à deux jours, permettant de présenter et de discuter les travaux, théoriques ou appliqués, à différents stades d'avancement. Cette année 2010, le 18ème atelier RàPC est organisé à Strasbourg, en amont des assises du GDR I3 (" Information, Interaction, Intelligence "). À cette occasion, l'atelier RàPC partage une demi-journée avec les rencontres du thème IAF " Intelligence Artificielle Fondamentale " du GDR I3. Le programme complet est ainsi constitué de neuf présentations, huit soumises à l'atelier RàPC et une soumise aux journées IAF. Ces présentations sont réparties en quatre sessions : une première session porte sur des applications du RàPC à l'espace et aux déplacements ; une deuxième session (en deux temps) regroupe différents travaux sur l'adaptation ; les deux autres sessions sont consacrées pour l'une à la réutilisation d'expériences et à la remémoration, et pour l'autre à la comparaison du RàPC à d'autres méthodes appuyées sur l'expérience

ICE-B 2010:proceedings of the International Conference on e-Business

The International Conference on e-Business, ICE-B 2010, aims at bringing together researchers and practitioners who are interested in e-Business technology and its current applications. The mentioned technology relates not only to more low-level technological issues, such as technology platforms and web services, but also to some higher-level issues, such as context awareness and enterprise models, and also the peculiarities of different possible applications of such technology. These are all areas of theoretical and practical importance within the broad scope of e-Business, whose growing importance can be seen from the increasing interest of the IT research community. The areas of the current conference are: (i) e-Business applications; (ii) Enterprise engineering; (iii) Mobility; (iv) Business collaboration and e-Services; (v) Technology platforms. Contributions vary from research-driven to being more practical oriented, reflecting innovative results in the mentioned areas. ICE-B 2010 received 66 submissions, of which 9% were accepted as full papers. Additionally, 27% were presented as short papers and 17% as posters. All papers presented at the conference venue were included in the SciTePress Digital Library. Revised best papers are published by Springer-Verlag in a CCIS Series book