Antichaos in a Class of Random Boolean Cellular Automata

A variant of Kauffman's model of cellular metabolism is presented. It is a randomly generated network of boolean gates, identical to Kauffman's except for a small bias in favor of boolean gates that depend on at most one input. The bias is asymptotic to 0 as the number of gates increases. Upper bounds on the time until the network reaches a state cycle and the size of the state cycle, as functions of the number of gates $n$, are derived. If the bias approaches 0 slowly enough, the state cycles will be smaller than $n^c$ for some $c<1$. This lends support to Kauffman's claim that in his version of random network the average size of the state cycles is approximately $n^{1/2}$.Comment: 12 pages. A uuencoded, tar-compressed postscipt file containing figures has been adde

Evaluation de Techniques de Traitement des Refusés pour l'Octroi de Crédit

We present the problem of "Reject Inference" for credit acceptance. Because of the current legal framework (Basel II), credit institutions need to industrialize their processes for credit acceptance, including Reject Inference. We present here a methodology to compare various techniques of Reject Inference and show that it is necessary, in the absence of real theoretical results, to be able to produce and compare models adapted to available data (selection of "best" model conditionnaly on data). We describe some simulations run on a small data set to illustrate the approach and some strategies for choosing the control group, which is the only valid approach to Reject Inference

Connectionnists Methods for Human Face Processing

We show in this paper how Neural Networks can be used for Human Face Processing. In Part I, we show how Neural Networks can be viewed as a particular class of Statistical models. We introduce learning as an estimation problem, then describe Multi-Layer Perceptrons (MLP) and Radial Basis Function (RBF) networks, widely used Neural Networks which we will use in Part~II, for face processing. We further present Vapnik's framework for learning, show the capacity/generalization dilemma and discuss its implications for Neural Network training and model selection. Vapnik's ideas lead to a new interesting class of classifier, Support Vector Machines, presented in section 3. We then discuss the combination of models and give a formalism which allows to cooperatively train multi-modular Neural Networks architectures. Finally, we present a multi-modular architecture to perform "Segmentation-Recognition in the loop". In Part II, we show how the presented models can be applied to build an efficient face localization and identification system. The face images are detected by scanning the scene with a retina feeding a hierarchical coarse-to-fine classifier. Detections are then identified in a small family of known persons

Modèles connexionnistes de l'apprentissage

Le Cun Y., Fogelman-Soulié Françoise. Modèles connexionnistes de l'apprentissage. In: Intellectica. Revue de l'Association pour la Recherche Cognitive, n°2-3, 1987/1. Apprentissage et machine. pp. 114-143

Towards Automatic Complex Feature Engineering

International audienc

AI & Human Values

International audienceThis chapter summarizes contributions made by Ricardo Baeza-Yates, Francesco Bonchi, Kate Crawford, Laurence Devillers and Eric Salobir in the session chaired by Françoise Fogelman-Soulié on AI & Human values at the Global Forum on AI for Humanity. It provides an overview of key concepts and definitions relevant for the study of inequalities and Artificial Intelligence. It then presents and discusses concrete examples of inequalities produced by AI systems, highlighting their variety and potential harmfulness. Finally, we conclude by discussing how putting human values at the core of AI requires answering many questions, still open for further research

Les théories de la complexité : autour de l'oeuvre d'Henri Atlan

462 pages, figuresDepuis quelques années, dans le monde scientifique, le mot de "complexité" ne désigne plus une difficulté de compréhension ou de la réalisation, mais bien un problème, un objet d'étude en soi, un programme de recherche systématique. Publications, colloques, instituts de recherche sur les "systèmes complexes" témoignent de la vitalité considérable de ce nouveau champ pluri- et interdisciplinaire? Le colloque, tenu à Cerisy en juin 1984, dont on trouvera ici les Actes, aura marqué une date dans la réflexion française de ce domaine, en réunissant autour d'Henri Atlan, dont les travaux ont été pionniers en la matière, des chercheurs venus des horizons les plus divers : mathématiques, informatique, intelligence artificielle, physique, sciences du vivant, sciences cognitives, sciences de l'homme et du social, philosophie (...