The idea of knowledge bases lies at the heart of symbolic, or "traditional," artificial intelligence. A knowledge-based system decides how to act by running formal reasoning procedures over a body of explicitly represented knowledge--a knowledge base. The system is not programmed for specific tasks; rather, it is told what it needs to know and expected to infer the rest.This book is about the logic of such knowledge bases. It describes in detail the relationship between symbolic representations of knowledge and abstract states of knowledge, exploring along the way the foundations of knowledge, knowledge bases, knowledge-based systems, and knowledge representation and reasoning. Assuming some familiarity with first-order predicate logic, the book offers a new mathematical model of knowledge that is general and expressive yet more workable in practice than previous models. The book presents a style of semantic argument and formal analysis that would be cumbersome or completely impractical with other approaches. It also shows how to treat a knowledge base as an abstract data type, completely specified in an abstract way by the knowledge-level operations defined over it.
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This book describes in detail the relationship between symbolic representations of knowledge and abstract states of knowledge, exploring along the way the foundations of knowledge, knowledge bases, knowledge-based systems, and knowledge representation and reasoning.
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In a book about the logical foundations of knowledge bases, it is probably a good idea to review if only briefly how concepts like knowledge, representation, reasoning, knowledge bases, and so on are understood informally within Artificial Intelligence (AI), and why so many researchers feel that these notions are important to the AI enterprise. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
distinct standard names, representable states, basic belief set, initial epistemic state, propositional subset, objective sentences, tautological entailment, subjective sentences, current epistemic state, finite consistent set, autoepistemic reasoning, prenex conjunctive normal form, stable expansions, autoepistemic logic, maximally consistent set, epistemic states, nested beliefs, prime implicates, admissible terms, objective formula, admissible substitution, ask operations, propositional case, belief implication, valid sentences New!
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Front Cover | Table of Contents | First Pages | Index | Surprise Me!
In a book about the logical foundations of knowledge bases, it is probably a good idea to review if only briefly how concepts like knowledge, representation, reasoning, knowledge bases, and so on are understood informally within Artificial Intelligence (AI), and why so many researchers feel that these notions are important to the AI enterprise. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
distinct standard names, representable states, basic belief set, initial epistemic state, propositional subset, objective sentences, tautological entailment, subjective sentences, current epistemic state, finite consistent set, autoepistemic reasoning, prenex conjunctive normal form, stable expansions, autoepistemic logic, maximally consistent set, epistemic states, nested beliefs, prime implicates, admissible terms, objective formula, admissible substitution, ask operations, propositional case, belief implication, valid sentences New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Surprise Me!
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This book cites 35
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7
books
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- Artificial Intelligence (Watts Library) by Robert L. Perry in Back Matter
- Computer Science (Watts Library) by Robert L. Perry in Back Matter
- Database Systems: Concepts, Languages and Architectures by Paolo Atzeni in Back Matter
- Principles of Artificial Intelligence by Nils J. Nilsson in Back Matter
- Reference and Modality (Readings in Philosophy Series) by Leonard Linsky in Back Matter
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- Semantics of a Networked World. Semantics for Grid Databases: First International IFIP Conference on Semantics of a Networked World: ICSNW 2004, ... Papers (Lecture Notes in Computer Science) on page 157
- Knowledge in Action: Logical Foundations for Specifying and Implementing Dynamical Systems by Raymond Reiter in Back Matter
- Knowledge Representation and Reasoning (The Morgan Kaufmann Series in Artificial Intelligence) by Ronald Brachman in Back Matter
- SOFSEM 2005: Theory and Practice of Computer Science: 31st Conference on Current Trends in Theory and Practice of Computer Science, Liptovský Ján, ... Computer Science and General Issues) by Maria Bieliková on page 39
- Hybrid Systems: Computation and Control: 8th International Workshop, HSCC 2005, Zurich, Switzerland, March 9-11, 2005, Proceedings (Lecture Notes in ... Computer Science and General Issues) on page 382
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