Introduction

Abstract

The construction of robust computational models integrating reasoning and learning is a key research challenge for artificial intelligence. Recently, this challenge was also put forward as a fundamental problem in computer science [255]. Such a challenge intersects with another long-standing entry in the research agenda of artificial intelligence: the integration of its symbolic and connectionist paradigms. Such integration has long been a standing enterprise, with implications for and applications in cognitive science and neuroscience [51, 66, 130, 178, 179, 238, 240, 247, 248, 250]. Further, the importance of efforts to bridge the gap between the connectionist and symbolic paradigms of artificial intelligence has also been widely recognised (see e.g. [51, 66, 229, 242, 243]).