Principles of knowledge representation and reasoning

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principles of knowledge representation and reasoning

Chitta Baral (Author of Knowledge Representation, Reasoning and Declarative Problem Solving)

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Introduction to Knowledge Representation and Reasoning

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July , The underlying approach of explicitly representing knowledge in a tangible form, suitable for processing by dedicated reasoning engines, is a fundamental component of many modern intelligent systems. It also contributes to the foundations of longstanding fields including automated planning, databases, and software engineering. The KR conference series is a leading forum for timely in-depth presentation of progress in the theory and principles underlying the representation and computational management of knowledge. The edition will be held as part of the Vienna Summer of Logic together with the Federated Conference on Logic, Logic Colloquium and other related events.

Knowledge representation incorporates findings from psychology [1] about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of reasoning , such as the application of rules or the relations of sets and subsets. Examples of knowledge representation formalisms include semantic nets , systems architecture , frames , rules, and ontologies. Examples of automated reasoning engines include inference engines , theorem provers , and classifiers. The KR conference series was established to share ideas and progress on this challenging field. Simon in These systems featured data structures for planning and decomposition.

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The conference provided a forum for reviewing the theory and principles underlying knowledge representation and reasoning. Topics covered range from reasoning about mental states and spatial reasoning with propositional logics to default logic as a query language. Comprised of 60 chapters, this book begins with a description of a formal language for representing and reasoning about time and action before turning to proof in context and how it can replace the most common uses of reflection principles. The reader is then introduced to reasoning with minimal models; belief ascription and mental-level modeling; and a unified framework for class-based representation formalisms. A general approach to specificity in default reasoning is also described, together with an ontology for engineering mathematics and the use of abduction to generate tests.

James Allen , Richard E. Fikes , Erik Sandewall. The proceedings of the Second International Conference on [title] held in Cambridge, Massachusetts, April , comprise 55 papers on topics including the logical specifications of reasoning behaviors and representation formalisms, comparative analysis of competing algorithms and formalisms, and ana. Temporal Reasoning and Narrative Conventions. Reflections about Reflection.

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