Integrated learning architectures

Abstract

Research in systems where learning is integrated to other components like problem solving, vision, or natural language is becoming an important topic for Machine Learning. Situations where learning methods are embedded or integrated into broader systems offers new theoretical challenges to ML and enlarge the potential range of ML applications. In this position paper we propose the research topic of integrated learning architectures as an initial discussion of the role of learning in intelligent systems. We review the current state of the art and characterise several dimensions along which integrated learning architectures may vary. This paper has been prepared as a position paper with the purpose of providing an initial common ground for discussion in the ECML-93 Workshop on Integrated Learning Architectures. The paper has been edited by E Plaza on the basis of the individual contributions of the authors.