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Principles of Knowledge Representation and Reasoning
The proceedings of the Second International Conference on [title] held in Cambridge, Massachusetts, April 1991, comprise 55 papers on topics including the logical specifications of reasoning behaviors and representation formalisms, comparative analysis of competing algorithms and formalisms, and ana
The Description Logic Handbook
Description Logics are a family of knowledge representation languages that have been studied extensively in Artificial Intelligence over the last two decades. They are embodied in several knowledge-based systems and are used to develop various real-life applications. The Description Logic Handbook provides a thorough account of the subject, covering all aspects of research in this field, namely: theory, implementation, and applications. Its appeal will be broad, ranging from more theoretically-oriented readers, to those with more practically-oriented interests who need a sound and modern understanding of knowledge representation systems based on Description Logics. The chapters are written by some of the most prominent researchers in the field, introducing the basic technical material before taking the reader to the current state of the subject, and including comprehensive guides to the literature. In sum, the book will serve as a unique reference for the subject, and can also be used for self-study or in conjunction with Knowledge Representation and Artificial Intelligence courses.
Changes of Problem Representation
The purpose of our research is to enhance the efficiency of AI problem solvers by automating representation changes. We have developed a system that improves the description of input problems and selects an appropriate search algorithm for each given problem. Motivation. Researchers have accumulated much evidence on the impor tance of appropriate representations for the efficiency of AI systems. The same problem may be easy or difficult, depending on the way we describe it and on the search algorithm we use. Previous work on the automatic im provement of problem descriptions has mostly been limited to the design of individual learning algorithms. The user has traditionally been responsible f...
Distributed Artificial Intelligence: Theory and Praxis
Distributed AI is the branch of AI concerned with how to coordinate behavior among a collection of semi-autonomous problem-solving agents: how they can coordinate their knowledge, goals and plans to act together, to solve joint problems, or to make individually or globally rational decisions in the face of uncertainty and multiple, conflicting perspectives. Distributed, coordinated systems of problem solvers are rapidly becoming practical partners in critical human problem-solving environments, and DAI is a rapidly developing field of both application and research, experiencing explosive growth around the world. This book presents a collection of articles surveying several major recent developments in DAI. The book focuses on issues that arise in building practical DAI systems in real-world settings, and covers work undertaken in a number of major research and development projects in the U.S. and in Europe. It provides a synthesis of recent thinking, both theoretical and applied, on major problems of DAI in the 1990s.
Knowledge Representation and Reasoning
Knowledge representation is at the very core of a radical idea for understanding intelligence. Instead of trying to understand or build brains from the bottom up, its goal is to understand and build intelligent behavior from the top down, putting the focus on what an agent needs to know in order to behave intelligently, how this knowledge can be represented symbolically, and how automated reasoning procedures can make this knowledge available as needed. This landmark text takes the central concepts of knowledge representation developed over the last 50 years and illustrates them in a lucid and compelling way. Each of the various styles of representation is presented in a simple and intuitive...
Principles of Knowledge Representation and Reasoning
Stringently reviewed papers presented at the October 1992 meeting held in Cambridge, Mass., address such topics as nonmonotonic logic; taxonomic logic; specialized algorithms for temporal, spatial, and numerical reasoning; and knowledge representation issues in planning, diagnosis, and natural langu
Generating Abstraction Hierarchies
Generating Abstraction Hierarchies presents a completely automated approach to generating abstractions for problem solving. The abstractions are generated using a tractable, domain-independent algorithm whose only inputs are the definition of a problem space and the problem to be solved and whose output is an abstraction hierarchy that is tailored to the particular problem. The algorithm generates abstraction hierarchies that satisfy the `ordered monotonicity' property, which guarantees that the structure of an abstract solution is not changed in the process of refining it. An abstraction hierarchy with this property allows a problem to be decomposed such that the solution in an abstract spa...
Readings in Agents
This book collects the most significant literature on agents in an attempt top forge a broad foundation for the field. Includes papers from the perspectives of AI, databases, distributed computing, and programming languages. The book will be of interest to programmers and developers, especially in Internet areas.
