Reasoning about knowledge—particularly the knowledge of agents who reason about the world and each other's knowledge—was once the exclusive province of philosophers and puzzle solvers. More recently, this type of reasoning has been shown to play a key role in a surprising number of contexts, from understanding conversations to the analysis of distributed computer algorithms. Reasoning About Knowledge is the first book to provide a general discussion of approaches to reasoning about knowledge and its applications to distributed systems, artificial intelligence, and game theory. It brings eight years of work by the authors into a cohesive framework for understanding and analyzing reasoning about knowledge that is intuitive, mathematically well founded, useful in practice, and widely applicable. The book is almost completely self-contained and should be accessible to readers in a variety of disciplines, including computer science, artificial intelligence, linguistics, philosophy, cognitive science, and game theory. Each chapter includes exercises and bibliographic notes.

Robert Aumann's career in game theory has spanned over research - from his doctoral dissertation in 1956 to papers as recent as January 1995. Threaded through all of Aumann's work (symbolized in his thesis on knots) is the study of relationships between different ideas, between different phenomena, and between ideas and phenomena. "When you look closely at one scientific idea", writes Aumann, "you find it hitched to all others. It is these hitches that I have tried to study". The papers are organized in several categories: general, knot theory, decision theory (utility and subjective probability), strategic games, coalitional games, and mathematical methods. Aumann has written an introduction to each of these groups that briefly describes the content and background of each paper, including the motivation and the research process, and relates it to other work in the collection and to work by others. There is also a citation index that allows readers to trace the considerable body of literature which cites Aumann's own work.

Knowledge representation is at the very core of a radical idea for understanding intelligence. This book talks about the central concepts of knowledge representation developed over the years. It is suitable for researchers and practitioners in database management, information retrieval, object-oriented systems and artificial intelligence.

The implications for philosophy and cognitive science of developments in statistical learning theory. In Reliable Reasoning, Gilbert Harman and Sanjeev Kulkarni—a philosopher and an engineer—argue that philosophy and cognitive science can benefit from statistical learning theory (SLT), the theory that lies behind recent advances in machine learning. The philosophical problem of induction, for example, is in part about the reliability of inductive reasoning, where the reliability of a method is measured by its statistically expected percentage of errors—a central topic in SLT. After discussing philosophical attempts to evade the problem of induction, Harman and Kulkarni provide an admirably clear account of the basic framework of SLT and its implications for inductive reasoning. They explain the Vapnik-Chervonenkis (VC) dimension of a set of hypotheses and distinguish two kinds of inductive reasoning. The authors discuss various topics in machine learning, including nearest-neighbor methods, neural networks, and support vector machines. Finally, they describe transductive reasoning and suggest possible new models of human reasoning suggested by developments in SLT.

This volume contains the proceedings of CONCURRENCY 88, an international conference on formal methods for distributed systems, held October 18-19, 1988 in Hamburg. CONCURRENCY 88 responded to great interest in the field of formal methods as a means of mastering the complexity of distributed systems. In addition, the impulse was determined by the fact that the various methodological approaches, such as constructive or property oriented methods, have not had an extensive comparative analysis nor have they been investigated with respect to their possible integration and their practical implications. The following topics were addressed: Specification Languages, Models for Distributed Systems, Verification and Validation, Knowledge Based Protocol Modeling, Fault Tolerance, Distributed Databases. The volume contains 12 invited papers and 14 contributions selected by the program committee. They were presented by authors from Austria, the Federal Republic of Germany, France, Israel, Italy, the Netherlands, the United Kingdom and the United States.