Authors: Simon Alford, Zenna Tavares, Kevin Ellis

Abstract: The concept of abstraction has been a recurring focus within artificial intelligence research. This paper makes the case for the continued importance of abstraction as a foundation of general learning and reasoning systems. We clarify a notion of and purpose for abstraction as yet unsatisfied by pure deep learning approaches, briefly review approaches to abstraction for program analysis, list a number of areas where state-of-the-art deep learning approaches stand to be improved by incorporating abstraction learning, and discuss some considerations of what it means to learn good abstractions.