Principles of Knowledge Representation and Reasoning contains the proceedings of the Fourth International Conference on Principles of Knowledge Representation and Reasoning (KR '94) held in Bonn, Germany, on May 24-27, 1994.
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. The book concludes by considering the use of natural language for knowledge representation and reasoning.
This monograph will be of interest to both students and practitioners in the fields of artificial intelligence and computer science.
Principles of Knowledge Representation and Reasoning contains the proceedings of the Fourth International Conference on Principles of Knowledge Representation and Reasoning (KR '94) held in Bonn, Germany, on May 24-27, 1994.
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. The book concludes by considering the use of natural language for knowledge representation and reasoning.
This monograph will be of interest to both students and practitioners in the fields of artificial intelligence and computer science.