The "Naive Physics Manifesto" of Pat Hayes (1978) proposes a large-scale project to develop a formal theory encompassing the entire knowledge of physics of naive reasoners, expressed in a declarative symbolic form. The theory is organized in clusters of closely interconnected concepts and axioms. More recent work on the representation of commonsense physical knowledge has followed a somewhat different methodology. The goal has been to develop a competence theory powerful enough to justify commonsense physical inferences, and the research is organized in microworlds, each microworld covering a small range of physical phenomena. In this article, I compare the advantages and disadvantages of the two approaches.

A full book, available for free in PDF form.From the preface:A major problem in artificial intelligence is to endow computers with commonsense knowledge of the world and with the ability to use that knowledge sensibly. A large body of research has studied this problem through careful analysis of typical examples of reasoning in a variety of commonsense domains. The immediate aim of this research is to develop a rich language for expressing commonsense knowledge, and inference techniques for carrying out commonsense reasoning. This book provides an introduction and a survey of this body of research. It is, to the best of my knowledge, the first book to attempt this.The book is designed to be used as a textbook for a one-semester graduate course on knowledge representation.Morgan Kaufmann

The AI lab at the Courant Institute at New York University (NYU) is pursuing many different areas of artificial intelligence (AI), including natural language processing, vision, common sense reasoning, information structuring, learning, and expert systems. Other groups in the Computer Science Department are studying such AI-related areas as text analysis, parallel Lisp and Prolog, robotics, low-level vision, and evidence theory.

Although the group at System Development Corp. (Paoli, Pennsylvania), techniques being studied should be widely applicable, we are with each group responsible for certain aspects of system specifically developing a system to understand paragraphlength design. Our groups are jointly responsible for integration of messages about equipment failures, with the aim of the next-generation text-processing system as part of the Defense summarizing each failure and assessing its impact. Advanced Research Projects Agency (DARPA) Strategic Several laboratory prototypes have been constructed for Computing Program (Grishman and Hirschman 1986). We aim to improve on these earlier a small question-answering system that answers simple systems through a combination of two techniques: the use of English queries about a student transcript database This system detailed domain knowledge to verify and complete our linguistic is used for teaching and as a preliminary test bed for analyses and the use of "forgiving" algorithms that some of our linguistic analysis techniques. Participants: Ralph Grishman (faculty); Tomasz Ksiezyk, To guide the development of our system, we selected a Ngo Thank Nhan, Michael Moore, and John Sterling corpus of messages describing the failure of one particular piece of equipment, a starting air compressor.