Automated Common-sense Spatial Reasoning: Still a Huge Challenge

Abstract

Achieving “commonsense reasoning” capabilities has been one of the goals of AI since its inception. However, as Marcus and Davis have recently argued, “Common sense is not just the hardest problem for AI; in the long run, it’s also the most important problem”. Moreover, it is generally accepted that space (and time) underlie much of what we regard as commonsense reasoning. Despite many successes in dealing with particular restricted types of spatial information, the development of a system capable of carrying out automated spatial reasoning of similar diversity to what one finds in ordinary natural language descriptions, seems to be a long way off. The chapter gives a general (though not comprehensive) overview of the goal of automating commonsense spatial reasoning by means of symbolic representations and reasoning. Existing work is surveyed, the nature of the goal clarified, and the problem analysed into seven interacting sub-problems.