Readings in Knowledge Representation
Ronald J. Brachman, Hector J. Levesque
M. Kaufmann Publishers, 1985 - Reference - 571 pages
In Artificial Intelligence, it is often said that the representation of knowledge is the key to the design of robust intelligent systems. In one form or another the principles of Knowledge Representation are fundamental to work in natural language processing, computer vision, knowledge-based expert systems, and other areas. The papers reprinted in this volume have been collected to allow the reader with a general technical background in AI to explore the subtleties of this key subarea. These seminal articles, spanning a quarter-century of research, cover the most important ideas and developments in the representation field. The editors introduce each paper, discuss its relevance and context, and provide an extensive bibliography of other work. "Readings in Knowledge Representation" is intended to serve as a complete sourcebook for the study of this crucial subject.
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Some Problems and NonProblems in Representation Theory
Epistemological Problems of Artificial Intelligence
Prologue to Reflection and Semantics in a Procedural Language
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A-KIND-OF advice taker algorithm Artificial Intelligence assertion associated believe Bobrow Brachman cognitive comparison note Conceptual Dependency context corresponding data structures deduction default defined definition described discussed domain encoded entities epistemological example explicit expressions fact first-order logic formal frame function goal Hayes human individual inference intensional interpretation involved John kind Knowledge Representation Knowledge Representation Enterprise linguistic logic machine match meaning mechanism memory model metatheory Minsky natural language network notation node notion object opaque context paper particular phone number pointer possible predicate calculus primitives problem procedures programming language properties proposition quantified question Quillian reasoning reference relations relationships relative clause represent representation language role rules scene Schank semantic memory semantic nets semantic network sentence simple situation specific superatom symbol taller than Bill TBox theorem theory things tion understanding Winograd