Machine learning research at the Laboratoire de Recherche en Informatique at Orsay, France

Abstract

This article provides a brief account with sketchy technical details of the major directions in machine learning research done at the Laboratoire de recherche en informatique (LRI) at Orsay University in France. References contain publications giving details on the projects described in this paper and on closely related works.Our research has several objectives: looking for a sound basis of the process of generalization from examples, using this to study conceptual clustering with automatic synthesis of descriptors; studying the nature and goodness of an explanation in the context of apprentice systems; and developing experimental learning systems based on these principles applied to various practical domains. The approach taken by our research group has evolved with time but is still mainly based on learning of concepts from examples using logic representations and techniques. It corresponds to a major goal of our group: to give a clear and rigorous picture, if not a theory, of the topics under investigation. Several aspects are persued at the same time: concept learning by generalization, developments of explanation‐based learning techniques, analogy reasoning, and automatic tuning of the description language. These different directions are related to or stimulated by different domains of tasks: learning of rule bases, games, computer‐aided teaching, learning in noisy environments, and so on. They are described in this article in the light of the main directions. The goal of a complete universal integrated system is still a far cry ahead, but as states a famous Chinese proverb: “The end lies in the way”.