Realism concerning a given domain of things is the view that the things in that domain exist, and are as they are, quite independently of anyone’s thought or experience of them. The realism which I am concerned with here is empirical realism, that is, realism concerning empirical things, which are the ordinary persisting things presented to us in our perception of the world around us. Empirical...

The question of how machines can be endowed with the ability to acquire and robustly manipulate commonsense knowledge is a fundamental scientific problem. Here we formulate an approach to this problem that we call knowledge infusion. We argue that robust logic offers an appropriate semantics for this endeavor because it supports provably efficient algorithms for a basic set of necessary learnin...

Reasoning about motion is an important part of common sense knowledge. The spatial and qualitative aspects of reasoning about motion through fret space arc studied through the construction of a program to perform such reasoning. An analog gcomctry rcprcscntation serves as a diagram, and descriptions of both the actual motion of a ball and envisioning are used in answering simple questions.

This paper describes an exercise in the formalization of commonsense with Answer Set Programming aimed at finding the answer to an interesting riddle, whose solution is not obvious to many people. Solving the riddle requires a considerable amount of commonsense knowledge and sophisticated knowledge representation and reasoning techniques, including planning and adversarial reasoning. Most impor...

The lack of adequate bases of commonsense or even lexical knowledge is perhaps the main obstacle to the development of highperformance, robust tools for semantic interpretation. It is also generally accepted that, notwithstanding the increasing availability in recent years of substantial hand-coded lexical resources such as WordNet and EuroWordNet, addressing the commonsense knowledge bottlenec...

There are various aspects of making computers understand natural language. Semantic parsing and reasoning on commonsense knowledge are the two important ones. Many NLU tasks such as question answering and co-reference resolution require semantic parsing of text and reasoning with different kinds of commonsense knowledge. In this work we present our progress towards these milestones of NLU. We d...

As a crucial part of natural language processing, event-centered commonsense inference task has attracted increasing attention. With given observed event, the intention and reaction people involved in event are required to be inferred with artificial intelligent algorithms. To solve this problem, sequence-to-sequence methods widely studied, where is first encoded into specific representation th...

The Spatial Semantic Hierarchy and its predecessor the TOUR model are theories of robot and human commonsense knowledge of large-scale space: the cognitive map. The focus of these theories is on how spatial knowledge is acquired from experience in the environment, and how it can be used effectively in spite of being incomplete and sometimes incorrect. This essay is a personal reflection on the ...

Abstract Algorithms based on deep network models are being used for many pattern recognition and decision-making tasks in robotics AI. Training these requires a large labeled dataset considerable computational resources, which not readily available domains. Also, it is difficult to explore the internal representations reasoning mechanisms of models. As step towards addressing underlying knowled...