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The ability to draw inferences is a central operation in any artificial intelligence system. Automated reasoning is therefore among the traditional disciplines in AI. Theory reasoning is about techniques for combining automated reasoning systems with specialized and efficient modules for handling domain knowledge called background reasoners. Connection methods have proved to be a good choice for implementing high-speed automated reasoning systems. They are the starting point in this monograph,in which several theory reasoning versions are defined and related to each other. A major contribution of the book is a new technique of linear completion allowing for the automatic construction of background reasoners from a wide range of axiomatically given theories. The emphasis is on theoretical investigations, but implementation techniques based on Prolog are also covered.

Automatic theorem proving --- Computer Science --- Engineering & Applied Sciences --- Automatic theorem proving. --- Theorema's--Automatische bewijsvoering --- Théorèmes--Démonstration automatique --- Automated theorem proving --- Theorem proving, Automated --- Theorem proving, Automatic --- Engineering. --- Computers. --- Mathematical logic. --- Artificial intelligence. --- Robotics. --- Automation. --- Robotics and Automation. --- Theory of Computation. --- Artificial Intelligence (incl. Robotics). --- Mathematical Logic and Formal Languages. --- Mathematical Logic and Foundations. --- Artificial intelligence --- Proof theory --- Information theory. --- Computer science. --- Logic, Symbolic and mathematical. --- Artificial Intelligence. --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Informatics --- Science --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Communication theory --- Communication --- Cybernetics --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Calculators --- Cyberspace --- Automatic factories --- Automatic production --- Computer control --- Engineering cybernetics --- Factories --- Industrial engineering --- Mechanization --- Assembly-line methods --- Automatic control --- Automatic machinery --- CAD/CAM systems --- Robotics --- Automation

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Geology, Stratigraphic --- Sedimentation and deposition --- Geology --- -Geology, Stratigraphic --- -Sedimentation and deposition --- Deposition and sedimentation --- Sedimentary processes --- Physical geology --- Age of rocks --- Rocks --- Stratigraphic geology --- Geognosy --- Geoscience --- Earth sciences --- Natural history --- Age --- EAR Earth Sciences --- Jurassic --- sediments --- Greece --- Jurassic Period --- Geology, Stratigraphic - Jurassic --- Geology - Greece - Argolis Peninsula --- EUROPE DU SUD --- GRECE, CRETE --- GEOLOGIE REGIONALE --- JURASSIQUE --- SECONDAIRE

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Few developments in the intellectual life of the past quarter-century have provoked more controversy than the attempt to engineer human-like intelligence by artificial means. Born of computer science, this effort has sparked a continuing debate among the psychologists, neuroscientists, philosophers,and linguists who have pioneered--and criticized--artificial intelligence. Are there general principles, as some computer scientists had originally hoped, that would fully describe the activity of both animal and machine minds, just as aerodynamics accounts for the flight of birds and airplanes? In the twenty substantial interviews published here, leading researchers address this and other vexing questions in the field of cognitive science.The interviewees include Patricia Smith Churchland (Take It Apart and See How It Runs), Paul M. Churchland (Neural Networks and Commonsense), Aaron V. Cicourel (Cognition and Cultural Belief), Daniel C. Dennett (In Defense of AI), Hubert L. Dreyfus (Cognitivism Abandoned), Jerry A. Fodor (The Folly of Simulation), John Haugeland (Farewell to GOFAI?), George Lakoff (Embodied Minds and Meanings), James L. McClelland (Toward a Pragmatic Connectionism), Allen Newell (The Serial Imperative), Stephen E. Palmer (Gestalt Psychology Redux), Hilary Putnam (Against the New Associationism), David E. Rumelhart (From Searching to Seeing), John R. Searle (Ontology Is the Question), Terrence J. Sejnowski (The Hardware Really Matters), Herbert A. Simon (Technology Is Not the Problem), Joseph Weizenbaum (The Myth of the Last Metaphor), Robert Wilensky (Why Play the Philosophy Game?), Terry A.Winograd (Computers and Social Values), and Lotfi A. Zadeh (The Albatross of Classical Logic). Speaking Minds can complement more traditional textbooks but can also stand alone as an introduction to the field.Originally published in 1995.The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.

Cognitive science. --- Scientists --- SCIENCE / Life Sciences / Biology. --- Science --- Philosophy of mind

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