It is a pleasure and an honor to be able to present this collection of papers to Ray Reiter on the occasion of his 60th birthday. To say that Ray's research has had a deep impact on the field of Artificial Intel ligence is a considerable understatement. Better to say that anyone thinking of do ing work in areas like deductive databases, default reasoning, diagnosis, reasoning about action, and others should realize that they are likely to end up proving corol laries to Ray's theorems. Sometimes studying related work makes us think harder about the way we approach a problem; studying Ray's work is as likely to make us want to drop our way of doing things and take up his. This is because more than a mere visionary, Ray has always been a true leader. He shows us how to proceed not by pointing from his armchair, but by blazing a trail himself, setting up camp, and waiting for the rest of us to arrive. The International Joint Conference on Ar tificial Intelligence clearly recognized this and awarded Ray its highest honor, the Research Excellence award in 1993, before it had even finished acknowledging all the founders of the field. The papers collected here sample from many of the areas where Ray has done pi oneering work. One of his earliest areas of application was databases, and this is re flected in the chapters by Bertossi et at. and the survey chapter by Minker.

John Pollock aims to construct a theory of rational decision making for real agents--not ideal agents. Real agents have limited cognitive powers, but traditional theories of rationality have applied only to idealized agents that lack such constraints. Pollock argues that theories of ideal rationality are largely irrelevant to the decision making of real agents. Thinking about Acting aims to provide a theory of "real rationality."

Specifying and implementing dynamical systems with the situation calculus. Modeling and implementing dynamical systems is a central problem in artificial intelligence, robotics, software agents, simulation, decision and control theory, and many other disciplines. In recent years, a new approach to representing such systems, grounded in mathematical logic, has been developed within the AI knowledge-representation community. This book presents a comprehensive treatment of these ideas, basing its theoretical and implementation foundations on the situation calculus, a dialect of first-order logic. Within this framework, it develops many features of dynamical systems modeling, including time, processes, concurrency, exogenous events, reactivity, sensing and knowledge, probabilistic uncertainty, and decision theory. It also describes and implements a new family of high-level programming languages suitable for writing control programs for dynamical systems. Finally, it includes situation calculus specifications for a wide range of examples drawn from cognitive robotics, planning, simulation, databases, and decision theory, together with all the implementation code for these examples. This code is available on the book's Web site.

Intended both as a text for advanced undergraduates and graduate students, and as a key reference work for AI researchers and developers, Logical Foundations of Artificial Intelligence is a lucid, rigorous, and comprehensive account of the fundamentals of artificial intelligence from the standpoint of logic. The first section of the book introduces the logicist approach to AI--discussing the representation of declarative knowledge and featuring an introduction to the process of conceptualization, the syntax and semantics of predicate calculus, and the basics of other declarative representations such as frames and semantic nets. This section also provides a simple but powerful inference procedure, resolution, and shows how it can be used in a reasoning system. The next several chapters discuss nonmonotonic reasoning, induction, and reasoning under uncertainty, broadening the logical approach to deal with the inadequacies of strict logical deduction. The third section introduces modal operators that facilitate representing and reasoning about knowledge. This section also develops the process of writing predicate calculus sentences to the metalevel--to permit sentences about sentences and about reasoning processes. The final three chapters discuss the representation of knowledge about states and actions, planning, and intelligent system architecture. End-of-chapter bibliographic and historical comments provide background and point to other works of interest and research. Each chapter also contains numerous student exercises (with solutions provided in an appendix) to reinforce concepts and challenge the learner. A bibliography and index complete this comprehensive work.

This reader collects and introduces important work in linguistics, computer science, artificial intelligence, and computational linguistics on the use of linguistic devices in natural languages to situate events in time: whether they are past, present, or future; whether they are real or hypothetical; when an event might have occurred, and how long it could have lasted. In focussing on the treatment and retrieval of time-based information it seeks to lay the foundation for temporally-aware natural language computer processing systems, for example those that process documents on the worldwide web to answer questions or produce summaries. The development of such systems requires the application of technical knowledge from many different disciplines. The book is the first to bring these disciplines together, by means of classic and contemporary papers in four areas: tense, aspect, and event structure; temporal reasoning; the temporal structure of natural language discourse; and temporal annotation. Clear, self-contained editorial introductions to each area provide the necessary technical background for the non-specialist, explaining the underlying connections across disciplines. A wide range of students and professionals in academia and industry will value this book as an introduction and guide to a new and vital technology. The former include researchers, students, and teachers of natural language processing, linguistics, artificial intelligence, computational linguistics, computer science, information retrieval (including the growing speciality of question-answering), library sciences, human-computer interaction, and cognitive science. Those in industry include corporate managers and researchers, software product developers, and engineers in information-intensive companies, such as on-line database and web-service providers.

This book gives detailed descriptions of the development of two large scale multiagent systems: Agent.Hospital and Agent.Enterprise. These two systems have been developed in close cooperation with more than 20 enterprises and hospitals. They demonstrate clearly that multiagent technology has a great potential for innovative information systems, if a high degree of flexibility of the overall systems is required, e.g. because human actors and technical systems exhibit a great degree of local autonomy, or if the work environment is highly dynamic.

This exciting new text reveals both the evolution of this programming paradigm since its inception and the impressively broad scope of current research in the field. The contributors to this book are all leading world experts in Logic Programming, and they deal with both theoretical and practical issues. They address such diverse topics as: computational molecular biology, machine learning, mobile computing, multi-agent systems, planning, numerical computing and dynamical systems, database systems, an alternative to the "formulas as types" approach, program semantics and analysis, and natural language processing. XXXXXXX Neuer Text Logic Programming was founded 25 years ago. This exciting book reveals both the evolution of this programming paradigm and its impressively broad scope of current research. The contributions by leading computer scientists deal with both theoretical and practical issues. They address diverse topics such as: computational molecular biology, machine learning, mobile computing, multi-agent systems, numerical computing and dynamical systems, database systems, program semantics, natural language processing, and promising future directions.