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. 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.
This book provides a systematic in-depth investigation of a class of multiple-context assumption-based multiagent reasoning problems, typical, e.g., for distributed planning, scheduling, and control. First, logical and architectural foundations are provided to construct the two systems XFRMS and MXFRMS allowing the development of more complex utilities. Then the technology developed for XFRMS in the single-agent case is further enhanced to the multiagent situation. The multiagent RMS MXFRMS provides, along with XFRMS, a solid foundation for building more complex utilities, such as plan or schedule maintenance systems. In the final chapter, the software engineer confronted with the task of building a practicable multiagent system can find a discussion of potential uses and future extensions of the systems provided.
This proceedings volume contains a selection of revised and extended papers presented at the Second International Workshop on Nonmonotonic and InductiveLogic, NIL '91, which took place at Reinhardsbrunn Castle, December 2-6, 1991. The volume opens with an extended version of a tutorial on nonmonotonic logic by G. Brewka, J. Dix, and K. Konolige. Fifteen selected papers follow, on a variety of topics. The majority of papers belong either to the area of nonmonotonic reasoning or to the field of inductive inference, but some papers integrate research from both areas. The first workshop in this series was held at the University of Karlsruhe in December 1990 and its proceedings were published as Lecture Notes in Artificial Intelligence Volume 543. The series of workshops was made possible by financial support from Volkswagen Stiftung, Hannover. This workshop was also supported by IBM Deutschland GmbH and Siemens AG.
This book constitutes the refereed proceedings of the 21st Annual German Conference on Artificial Intelligence, KI-97, held in Freiburg, Germany, in September 1997. The volume presents revised versions of 26 full papers and 10 posters selected from around 70 submissions from more than 15 countries. Also included are three excellent invited contributions by Anthony G. Cohn, Kurt Konolige, and Pat Langley. The papers are organized in topical sections on theorem proving, nonclassical logics, knowledge representation, spatial reasoning, computational linguistics, computer perception and neural nets, and on planning, diagnosis and search.
This book constitutes the refereed proceedings of the Second International Workshop on Computer Vision Systems, ICVS 2001, held in Vancouver, Canada, in July 2001. The 20 revised full papers presented were carefully reviewed and selected from 30 submissions. The papers are organized in topical sections on architectures for computer vision systems, tracking, autonomous driving, real-time vision modules, recognition, and exploration and navigation.
The papers collected in this book cover a wide range of topics in asymptotic statistics. In particular up-to-date-information is presented in detection of systematic changes, in series of observation, in robust regression analysis, in numerical empirical processes and in related areas of actuarial sciences and mathematical programming. The emphasis is on theoretical contributions with impact on statistical methods employed in the analysis of experiments and observations by biometricians, econometricians and engineers.
This proceedings volume contains a selection of revised and extended papers presented at the Second International Workshop on Nonmonotonic and InductiveLogic, NIL '91, which took place at Reinhardsbrunn Castle, December 2-6, 1991. The volume opens with an extended version of a tutorial on nonmonotonic logic by G. Brewka, J. Dix, and K. Konolige. Fifteen selected papers follow, on a variety of topics. The majority of papers belong either to the area of nonmonotonic reasoning or to the field of inductive inference, but some papers integrate research from both areas. The first workshop in this series was held at the University of Karlsruhe in December 1990 and its proceedings were published as Lecture Notes in Artificial Intelligence Volume 543. The series of workshops was made possible by financial support from Volkswagen Stiftung, Hannover. This workshop was also supported by IBM Deutschland GmbH and Siemens AG.
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