Handbook of Knowledge Representation: Volume 1 (Foundations of Artificial Intelligence, Volume 1) - Tapa dura

Reseña del editor

Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems.

This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering.

This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI.

Reseña del editor

Knowledge Representation, which lies at the core of Artificial Intelligence, is concerned with encoding knowledge on computers to enable systems to reason automatically. "The Handbook of Knowledge Representation" is an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. This book is an essential resource for students, researchers and practitioners in all areas of Artificial Intelligence. It makes your computer smarter. It offers to handle qualitative and uncertain information; and improve computational tractability to solve your problems easily.