Artificial Intelligence – serie

Explores how artificial intelligence is currently being used in the real world, including in health care, retail, manufacturing, and homes. Clear text, vibrant photos, and helpful infographics make this book an accessible and engaging read.

This monograph provides logical foundations and a uniform description for nonmonotonic reasoning and belief change. The approach to both these subjects is based on a powerful notion of an epistemic state that subsumes both existing models for nonmonotonic inference and current models for belief change. Many results and constructions in the book are completely new and have not appeared earlier in the literature. The book is primarily intended for experts in Artificial Intelligence and Knowledge Representation who are interested in tools for describing commonsense reasoning tasks as well as in representation capabilities of such tools. It is also of interest to general logicians.

This monograph provides a thorough analysis of two importantformalisms for nonmonotonic reasoning: default logic andmodal nonmonotonic logics. It is also shown how they arerelated to each other and how they provide the formalfoundations for logic programming. The discussion isrigorous, and all main results are formally proved. Many ofthe results are deep and surprising, some of them previouslyunpublished. The book has three parts, on default logic, modalnonmonotonic logics, and connections and complexity issues,respectively. The study of general default logic is followedby a discussion of normal default logic and its connectionsto the closed world assumption, and also a presentation ofrelated aspects of logic programming. The general theory ofthe family of modal nonmonotonic logics introduced byMcDermott and Doyle is followed by studies of autoepistemiclogic, the logic of reflexive knowledge, and the logic ofpure necessitation, and also a short discussion ofalgorithms for computing knowledge and belief sets. Thethird part explores connections between default logic andmodal nonmonotonic logics and contains results on thecomplexity of nonmonotonic reasoning.The ideas are presented with an elegance and unity ofperspective that set a new standard of scholarship for booksin this area, and the work indicates that the field hasreached a very high level of maturity and sophistication. The book is intended as a reference on default logic,nonmonotonic logics, and related computational issues, andis addressed to researchers, programmers, and graduatestudents in the Artificial Intelligence community.

Verbmobil is the result of eight years of intensive research in a large speech-to-speech translation project, executed by a consortium comprising nineteen academic and four industrial partners. The system that was developed by more than 100 researchers and engineers handles dialogs in three business-oriented domains, with translation between three languages: German, English, and Japanese. Verbmobil deals with spontaneous speech, which includes realistic repair phenomena, and uses deep semantic analysis to recognize a speaker's slips and to translate what he tried to say rather than what he actually said. - This book gives the first comprehensive overview of the results of this unique and seminal project in human language technology. Contributions by leading scientists in speech and language technology look at the component technologies that make Verbmobil the most advanced speech-to-speech translation system worldwide and a landmark project in the history of natural language processing.

The main subject and objective of this book are logical foundations of non­ monotonic reasoning. This bears a presumption that there is such a thing as a general theory of non monotonic reasoning, as opposed to a bunch of systems for such a reasoning existing in the literature. It also presumes that this kind of reasoning can be analyzed by logical tools (broadly understood), just as any other kind of reasoning. In order to achieve our goal, we will provide a common logical basis and semantic representation in which different kinds of non monotonic reasoning can be interpreted and studied. The suggested framework will subsume ba­ sic forms of nonmonotonic inference, including not only the usual skeptical one, but also various forms of credulous (brave) and defeasible reasoning, as well as some new kinds such as contraction inference relations that express relative independence of pieces of data. In addition, the same framework will serve as a basis for a general theory of belief change which, among other things, will allow us to unify the main approaches to belief change existing in the literature, as well as to provide a constructive view of the semantic representation used. This book is a monograph rather than a textbook, with all its advantages (mainly for the author) and shortcomings (for the reader).

Verbmobil is the result of eight years of intensive research in a large speech-to-speech translation project, executed by a consortium comprising nineteen academic and four industrial partners. The system that was developed by more than 100 researchers and engineers handles dialogs in three business-oriented domains, with translation between three languages: German, English, and Japanese. Verbmobil deals with spontaneous speech, which includes realistic repair phenomena, and uses deep semantic analysis to recognize a speaker's slips and to translate what he tried to say rather than what he actually said. - This book gives the first comprehensive overview of the results of this unique and seminal project in human language technology. Contributions by leading scientists in speech and language technology look at the component technologies that make Verbmobil the most advanced speech-to-speech translation system worldwide and a landmark project in the history of natural language processing.

Logic Programming was founded 25 years ago. This exciting new text reveals both the evolution of this programming paradigm since its inception and the impressively broad scope of current research in Logic Programming. The contributions to the book 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. The contributors are all leading world experts in Logic Programming and their contributions were all invited and refereed.

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.

"The central fact is that we are planning agents." (M. Bratman, Intentions, Plans, and Practical Reasoning, 1987, p. 2) Recent arguments to the contrary notwithstanding, it seems to be the case that people-the best exemplars of general intelligence that we have to date­ do a lot of planning. It is therefore not surprising that modeling the planning process has always been a central part of the Artificial Intelligence enterprise. Reasonable behavior in complex environments requires the ability to consider what actions one should take, in order to achieve (some of) what one wants­ and that, in a nutshell, is what AI planning systems attempt to do. Indeed, the basic description of a plan generation algorithm has remained constant for nearly three decades: given a desciption of an initial state I, a goal state G, and a set of action types, find a sequence S of instantiated actions such that when S is executed instate I, G is guaranteed as a result. Working out the details of this class of algorithms, and making the elabora­ tions necessary for them to be effective in real environments, have proven to be bigger tasks than one might have imagined.

With the rapid growth in the use of computers to manipulate, process, and reason about multimedia data, the problem of how to store and retrieve such data is becoming increasingly important. Thus, although the field of multimedia database systems is only about 5 years old, it is rapidly becoming a focus for much excitement and research effort. Multimedia database systems are intended to provide unified frameworks for requesting and integrating information in a wide variety of formats, such as audio and video data, document data, and image data. Such data often have special storage requirements that are closely coupled to the various kinds of devices that are used for recording and presenting the data, and for each form of data there are often multiple representations and multiple standards - all of which make the database integration task quite complex. Some of the problems include: - what a multimedia database query means - what kinds of languages to use for posing queries - how to develop compilers for such languages - how to develop indexing structures for storing media on ancillary devices - data compression techniques - how to present and author presentations based on user queries. Although approaches are being developed for a number of these problems, they have often been ad hoc in nature, and there is a need to provide a princi­ pled theoretical foundation.

This monograph describes a methodology for the design of knowledge-based systems. A knowledge-based system contains knowledge as well as information and data. The information and data in such a system can be modelled and imple­ mented as a database. The knowledge in such a system can be implemented either in a programming language or in an expert systems shell. This methodology has two distinguishing features. First, it is "unified". A unified methodology repre­ sents the data, information and knowledge in a homogeneous manner, as well as the relationships between them. Second, the methodology builds a maintenance mechanism into the design. In knowledge engineering terms, the representation used by this methodology to model knowledge bases applies equally to databases. In database terms, the representation used by this methodology to model databases applies equally to the database rules. The unified methodology unifies the design of the "knowledge base compo­ nent" and the "database component". "Unification" is achieved in five senses.

The primary aim of this monograph is to provide a formal framework for the representation and management of uncertainty and vagueness in the field of artificial intelligence. It puts particular emphasis on a thorough analysis of these phenomena and on the development of sound mathematical modeling approaches. Beyond this theoretical basis the scope of the book includes also implementational aspects and a valuation of existing models and systems. The fundamental ambition of this book is to show that vagueness and un­ certainty can be handled adequately by using measure-theoretic methods. The presentation of applicable knowledge representation formalisms and reasoning algorithms substantiates the claim that efficiency requirements do not necessar­ ily require renunciation of an uncompromising mathematical modeling. These results are used to evaluate systems based on probabilistic methods as well as on non-standard concepts such as certainty factors, fuzzy sets or belief functions. The book is intended to be self-contained and addresses researchers and practioneers in the field of knowledge based systems. It is in particular suit­ able as a textbook for graduate-level students in AI, operations research and applied probability. A solid mathematical background is necessary for reading this book. Essential parts of the material have been the subject of courses given by the first author for students of computer science and mathematics held since 1984 at the University in Braunschweig.

When I first participated in exploring theories of nonmonotonic reasoning in the late 1970s, I had no idea of the wealth of conceptual and mathematical results that would emerge from those halting first steps. This book by Wiktor Marek and Miroslaw Truszczynski is an elegant treatment of a large body of these results. It provides the first comprehensive treatment of two influen­ tial nonmonotonic logics - autoepistemic and default logic - and describes a number of surprising and deep unifying relationships between them. It also relates them to various modal logics studied in the philosophical logic litera­ ture, and provides a thorough treatment of their applications as foundations for logic programming semantics and for truth maintenance systems. It is particularly appropriate that Marek and Truszczynski should have authored this book, since so much of the research that went into these results is due to them. Both authors were trained in the Polish school of logic and they bring to their research and writing the logical insights and sophisticated mathematics that one would expect from such a background. I believe that this book is a splendid example of the intellectual maturity of the field of artificial intelligence, and that it will provide a model of scholarship for us all for many years to come. Ray Reiter Department of Computer Science University of Toronto Toronto, Canada M5S 1A4 and The Canadian Institute for Advanced Research Table of Contents 1 1 Introduction .........