A formal, foundational approach to autonomous knowledge acquisition is presented. In particular, “learning from examples” and “learning from being told” and the relation of these approaches to first-order representation systems are investigated. It is assumed initially that the only information available for acquisition is a stream of facts, or ground atomic formulae, describing a domain. On the basis of this information, hypotheses expressed in set-theoretic terms and concerning the application domain may be proposed. As further instances are received, the hypothesized relations may be modified or discarded, and new relations formed. The intent though is to characterize those hypotheses that may potentially be formed, rather than to specify the subset of the hypotheses that, for whatever reason, should be held.#R##N##R##N##R##N##R##N#Formal systems are derived by means of which the set of potential hypotheses is precisely specified, and a procedure is derived for restoring the consistency of a set of hypotheses after conflicting evidence is encountered. In addition, this work is extended to where a learning system may be “told” arbitrary sentences concerning a domain. Included in this is an investigation of the relation between acquiring knowledge and reasoning deductively. However, the interaction of these approaches leads to immediate difficulties which likely require informal, pragmatic techniques for their resolution. The overall framework is intended both as a foundation for investigating autonomous approaches to learning and as a basis for the development of such autonomous systems.#R##N##R##N##R##N##R##N#Une approche de base formelle a l' acquisition autonome de connaissances est presentee. l' apprentissage a partir d';exemples et a partir de directives ainsi que la relation de ces deux approches avec les systemes de repressentation logique des connaissances, sont etudies plus particulierement. En ce qui conceme l' acquisition des connaissances, on presume d';abord que la seule information disponible est une succession de faits, ou formules atomiques de basse, decrivant un domaine. En partant de cette information, il est possible de proposer des hypotheses exprimees en termes ensemblistes et reliees au domaine d';application. Au fur et a mesure que des exemples se presentent, les relations ayant fait l' objet d';hypotheses peuvent etre modifyees ou rejetees et de nouvelles relations peuvent etre formees. Cependant, le but est de caracteriser les hypotheses qui pourraient ětre formees plutot que de specifier les sous-ensembles d';hypotheses qui, pour une raison ou l' autre, devraient ětre retenues. Des systemes formels sont obtenus, au moyen desquels l' ensemble des hypotheses possibles est precisement specifie; une procedure est ensuite etablie pour retablir l' uniformite dans un ensemble d';hypotheses apres la rencontre d';elements conflictuels. Cette etude s'applique egalement aux points strategiques des systemes d';apprentissage ou des directives arbitraires concemant les domaines peuvent ětre inserees. Elle comprend entre autres, une investigation de la relation entre l' acquisition de connaissances et le raisonnement deductif. Cependant, l' interaction de ces methodes entraine des difficultes immediates qui doivent ětre resolues a l' aide de techniques pragmatiques informelles. La structure globale est consideree comme une base a la fois pour l' investigation des approches autonomes a l' apprentissage et pour le developpement de tels septemes.
['James P. Delgrande']
A foundational approach to autonomous knowledge acquisition