This book constitutes the refereed proceedings of the International Conference on Analytic Tableaux and Related Methods, TABLEAUX'97, held in Pont-a-Mousson, France, in May 1997.
The volume presents 22 revised full papers selected from a total of 49 submissions. Also included are two invited papers and two system descriptions. The volume covers the whole spectrum of tableaux-based theorem proving and its applications including theoretical foundations, methodological issues, implementation techniques, and system development. Besides classical logics, among the logics dealt with are modal, intuitionistic, many-valued, and temporal logic.

This book constitutes the refereed proceedings of the First International Joint Conference on Qualitative and Quantitative Practical Reasoning, ECSQARU-FAPR'97, held in Bad Honnef, Germany, in June 1997.
The volume presents 33 revised full papers carefully selected for inclusion in the book by the program committee as well as 12 invited contributions. Among the various aspects of human practical reasoning addressed in the papers are nonmonotonic logics, default reasoning, modal logics, belief function theory, Bayesian networks, fuzzy logic, possibility theory, inference algorithms, dynamic reasoning with partial models, and user modeling approaches.

This book constitutes the refereed proceedings of the Third European Workshop on Case-Based Reasoning, EWCBR-96, held in Lausanne, Switzerland, in November 1996.
Case-based reasoning is an appealing technique for dealing with the knowledge acquisition bottleneck in computer applications; solutions to new problems are found by adapting similar experience from the past, called cases. The 38 revised full papers presented were carefully selected from a broad variety of submissions after a thorough refereeing process. The volume refleats the state of the art in case-based reasoning research and applications.

A fundamental objective of Artificial Intelligence (AI) is the creation of in telligent computer programs. In more modest terms AI is simply con cerned with expanding the repertoire of computer applications into new domains and to new levels of efficiency. The motivation for this effort comes from many sources. At a practical level there is always a demand for achieving things in more efficient ways. Equally, there is the technical challenge of building programs that allow a machine to do something a machine has never done before. Both of these desires are contained within AI and both provide the inspirational force behind its development. In terms of satisfying both of these desires there can be no better example than machine learning. Machines that can learn have an in-built effi ciency. The same software can be applied in many applications and in many circumstances. The machine can adapt its behaviour so as to meet the demands of new, or changing, environments without the need for costly re-programming. In addition, a machine that can learn can be ap plied in new domains with the genuine potential for innovation. In this sense a machine that can learn can be applied in areas where little is known about possible causal relationships, and even in circumstances where causal relationships are judged not to exist. This last aspect is of major significance when considering machine learning as applied to fi nancial forecasting."

This book constitutes the refereed proceedings of the 7th International Conference on Database and Expert Systems Applications, DEXA '96, held in Zurich, Switzerland, in September 1996.
The 77 revised full papers included were selected from a total of nearly 200 submissions. They report on a broad spectrum of advanced applications and the design of database and expert systems. Among the topics addressed are object-oriented databases, active databases, temporal databases, transactions and concurrency, relational databases, CSCW and workflow systems, parallel and distributed systems, expert systems, knowledge-based systems, and information retrieval.

This book constitutes the refereed proceedings of the 8th European Workshop on Modelling Autonomous Agents in a Multi-Agent World, MAAMAW'97, held in Ronneby, Sweden, in May 1997.
MAAMAW'97 is devoted to multi-agent rationality, thus reflecting the fact that there is presently a transition in the multi-agent community from the study of individual rationality to the study of group rationality. The volume presents 15 revised full papers selected from a total of 51 submissions; also included are the abstracts of three invited talks. The volume covers all current issues in multi-agent rationality.

This book constitutes the refereed proceedings of the First International Workshop on Cooperative Information Agents - DAI Meets Databases, CIA-97, held in Kiel, Germany, in February 1997.
The book opens with 6 invited full papers by internationally leading researchers surveying the state of the art in the area. The 16 revised full research papers presented were carefully selected during a highly competitive round of reviewing. The papers are organized in topical sections on databases and agent technology, agents for database search and knowledge discovery, communication and cooperation among information agents, and agent-based access to heterogeneous information sources.

This book is based on the second International Workshop on Agent Theories, Architectures, and Languages, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95 in Montreal, Canada in August 1995.
The 26 papers are revised final versions of the workshop presentations selected from a total of 54 submissions; also included is a comprehensive introduction, a detailed bibliography listing 355 relevant publications, and a subject index. The book is structured into seven sections, reflecting the most current major directions in agent-related research. Together with its predecessor, Intelligent Agents, published as volume 890 in the LNAI series, this book provides a timely and comprehensive state-of-the-art report.

This book is based on the author's PhD thesis which was selected during the 1993 ACM Doctoral Dissertation Competition as one of the three best submissions.
The focus of this work is on the issue of availability in distributed file systems. It presents the important new technique called disconnected operation, in which clients mask failures and voluntary network detachments by emulating the functionality of servers where actual server-oriented solutions are inadequate. This permits client operation even under complete isolation from the server; the clean integration of mobile computers into the system is an important side-effect of the new technique. The design and implementation of disconnected file service in a working system, the Coda file system, is described in detail.

This book presents the refereed proceedings of the 9th European Knowledge Acquisition Workshop, EKAW '96, held in Nottingham, UK, in May 1996.
The 23 revised full papers included address the most relevant theoretical and applicational aspects of knowledge acquisition with a certain emphasis on the acquisition of knowledge for the modelling or automation of complex problem-solving behaviour. The volume is organized in sections on theoretical and general issues, eliciting knowledge from textual or other sources, data-mining, group elicitation, and planning.

This volume constitutes the proceedings of the 6th International Conference on Database and Expert Systems Applications, DEXA '95, held in London, UK in September 1995.
The 60 full revised papers presented in the volume were carefully selected from a total of almost 200 submissions and give a comprehensive view over advanced applications of information systems. Among the topics covered are object-oriented databases, advanced database applications, parallel and distributed systems, object-oriented modeling, information retrieval, theoretical aspects, extended relational databases, expert and knowledge-based systems, and physical aspects.

This book is the final report on a comprehensive basic research project, named GOSLER on algorithmic learning for knowledge-based systems supported by the German Federal Ministry of Research and Technology during the years 1991 - 1994. This research effort was focused on the study of fundamental learnability problems integrating theoretical research with the development of tools and experimental investigation.
The contributions by 11 participants in the GOSLER project is complemented by contributions from 23 researchers from abroad. Thus the volume provides a competent introduction to algorithmic learning theory.

This book presents a topical selection of full refereed research papers presented during the 5th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU '94, held in Paris, France in July 1994. The topical focus is on the role of uncertainty in the contruction of intelligent computing systems and it is shown how the concepts of AI, neural networks, and fuzzy logic can be utilized for that purpose.
In total, there are presented 63 thoroughly revised papers organized in sections on fundamental issues; theory of evidence; networks, probabilistic, statistical, and informational methods; possibility theory, logics, chaos, reusability, and applications.

This volume coherently present 24 thoroughly revised full papers accepted for the ECAI-94 Workshop on Agent Theories, Architectures, and Languages.
There is currently considerable interest, from both the AI and the mainstream CS communities, in conceptualizing and building complex computer systems as collections of intelligent agents. This book is devoted to theoretical and practical aspects of architectural and language-related design and implementation issues of software agents. Particularly interesting is the comprehensive survey by the volume editors, which outlines the key issues and indicates, via a comprehensive bibliography, topics for further reading. In addition, a glossary of key terms in this emerging field and a comprehensive subject index is included.

This book introduces the concept of software architecture as one of the cornerstones of software in modern cars. Following a historical overview of the evolution of software in modern cars and a discussion of the main challenges driving that evolution, Chapter 2 describes the main architectural styles of automotive software and their use in cars' software. Chapter 3 details this further by presenting two modern architectural styles, i.e. centralized and federated software architectures. In Chapter 4, readers will find a description of the software development processes used to develop software on the car manufacturers' side. Chapter 5 then introduces AUTOSAR - an important standard in automotive software. Chapter 6 goes beyond simple architecture and describes the detailed design process for automotive software using Simulink, helping readers to understand how detailed design links to high-level design. The new chapter 7 reports on how machine learning is exploited in automotive software e.g. for image recognition and how both on-board and off-board learning are applied. Next, Chapter 8 presents a method for assessing the quality of the architecture - ATAM (Architecture Trade-off Analysis Method) - and provides a sample assessment, while Chapter 9 presents an alternative way of assessing the architecture, namely by using quantitative measures and indicators. Subsequently Chapter 10 dives deeper into one of the specific properties discussed in Chapter 8 - safety - and details an important standard in that area, the ISO/IEC 26262 norm. Lastly, Chapter 11 presents a set of future trends that are currently emerging and have the potential to shape automotive software engineering in the coming years. This book explores the concept of software architecture for modern cars and is intended for both beginning and advanced software designers. It mainly aims at two different groups of audience - professionals working with automotive software who need to understand concepts related to automotive architectures, and students of software engineering or related fields who need to understand the specifics of automotive software to be able to construct cars or their components. Accordingly, the book also contains a wealth of real-world examples illustrating the concepts discussed and requires no prior background in the automotive domain. Compared to the first edition, besides the two new chapters 3 and 7 there are considerable updates in chapters 5 and 8 especially.

This volume comprises a selection of the key papers presented at the Eighth European Knowledge Acquisition Workshop (EKAW '94), held in Hoegaarden, Belgium in September 1994.
The book demonstrates that work in the mainstream of knowledge acquisition leads to useful practical results and puts the knowledge acquisition enterprise in a broader theoretical and technological context. The 21 revised full papers are carefully selected key contributions; they address knowledge modelling frameworks, the identification of generic components, methodology aspects, and architectures and applications. The volume opens with a substantial preface by the volume editors surveying the contents.

The objective of this book is two-fold. Firstly, it is aimed at bringing to gether key research articles concerned with methodologies for knowledge discovery in databases and their applications. Secondly, it also contains articles discussing fundamentals of rough sets and their relationship to fuzzy sets, machine learning, management of uncertainty and systems of logic for formal reasoning about knowledge. Applications of rough sets in different areas such as medicine, logic design, image processing and expert systems are also represented. The articles included in the book are based on selected papers presented at the International Workshop on Rough Sets and Knowledge Discovery held in Banff, Canada in 1993. The primary methodological approach emphasized in the book is the mathematical theory of rough sets, a relatively new branch of mathematics concerned with the modeling and analysis of classification problems with imprecise, uncertain, or incomplete information. The methods of the theory of rough sets have applications in many sub-areas of artificial intelligence including knowledge discovery, machine learning, formal reasoning in the presence of uncertainty, knowledge acquisition, and others. This spectrum of applications is reflected in this book where articles, although centered around knowledge discovery problems, touch a number of related issues. The book is intended to provide an important reference material for students, researchers, and developers working in the areas of knowledge discovery, machine learning, reasoning with uncertainty, adaptive expert systems, and pattern classification."

This volume constitutes the proceedings of the 5th International Conference on Database and Expert Systems Applications (DEXA '94), held in Athens, Greece in September 1994. The 78 papers presented were selected from more than 300 submissions and give a comprehensive view of advanced applications of databases and expert systems. Among the topics covered are object-oriented, temporal, active, geographical, hypermedia and distributed databases, data management, cooperative office applications, object-oriented modelling, industrial applications, conceptual modelling, legal systems, evolving environments, knowledge engineering, information retrieval, advanced querying, medical systems, and CIM.

Knowledge representation research is not only formal, it is also descriptiveand normative. Its aim is to implement a formal system which captures a practically relevant body of cognitive faculties employed by humans and capitalizes on its technical strength to extend human knowledge representation and reasoning capabilities. In this monograph, the author develops formalisms for his own notion of a vivid knowledge representation and reasoning system, characterized by the presence of two kinds of negation (weak and strong) and the requirements of restricted reflexivity, constructivity, and non-explosiveness. The book is based on work carried out within an interdisciplinary research project at the Free University of Berlin.

This volume constitutes the proceedings of the 4th International Conference on Database and Expert Systems Applications (DEXA), held in Prague, Czech Republic, in September 1993. Traditionally the objective of the DEXA conferences is to serve as an international forum for the discussion and exchange of research results and practical experinece among theoreticians and professionals working in the field of database and artificial intelligence technologies. Despite the fact that in the conference title the applications aspect is mentioned explicitly, the theoretical and the practical points of view in the field are well-balanced in the program of DEXA'93. The growing importance of the conference series is outlined by the remarkably high number of 269 submissions and by the support given by renown organizations. DEXA'93 is held for the first time outside the former GDR in an East-European country, and is essentially contributing to the advancement of the East-West scientific cooperation in the field of database and AI systems. This proceedings contains the 78 contributed papers carefully selected by an international program committee with thesupport of a high number of subreferees. The volume is organized in sectionson data models, distributed databases, advanced database aspects, database optimization and performance evaluation, spatial and geographic databases, expert systems and knowledge engineering, legal systems, other database and artificial intelligence applications, software engineering, and hypertext/hypermedia and user interfaces.

The Database and Expert Systems Application -DEXA - conferences are mainly oriented to establish a state-of-the art forum on Database and Expert System applications. But Practice without Theory has no sense, as Leonardo said five centuries ago. In this Conference we try a comprornise between these two complementary aspects. A total of 5 sessions are application-oriented, ranging from classical applications to more unusual ones in Software Engineering. Recent research aspects in Databases, such as activity, deductivity and/or Object Orientation are also present in DEXA 92, as weIl as the implication of the new "data models" such as OO-Model, Deductive Model, etc .. included in the Modelling sessions. Other areas of interest, such as Hyper-Text and Multimedia application, together with the classical field of Information Retrieval are also considered. FinaIly, Implementation Apects are reflected in very concrete fields. A total of of nearly 200 papers submitted from all over the world were sent to DEXA 92. Only 90 could be accepted. A Poster session has also been establishcd. DEXA 90 was held in Vienna, Austria; DEXA 91 in Berlin, Germany; and DEXA 92 will take place in Valencia, Spain, where we are celebrating the discovery of thc New World just five centurics ago, in Leonardo's age. Both the quality of the Conference and the compromise between Practice and Thcory are duc to the credit of all the DEXA 92 authors.

Artificial Intelligence for Improved Patient Outcomes provides new, relevant, and practical information on what AI can do in healthcare and how to assess whether AI is improving health outcomes. With clear insights and a balanced approach, this innovative book offers a one-stop guide on how to design and lead pragmatic real-world AI studies that yield rigorous scientific evidence-all in a manner that is safe and ethical. Daniel Byrne, Director of Artificial Intelligence Research at AVAIL (the Advanced Vanderbilt Artificial Intelligence Laboratory) and author of landmark pragmatic studies published in leading medical journals, shares four decades of experience as a biostatistician and AI researcher. Building on his first book, Publishing Your Medical Research, the author gives the reader the competitive advantage in creating reproducible AI research that will be accepted in prestigious high-impact medical journals. Provides easy-to-understand explanations of the key concepts in using and evaluating AI in medicine. Offers practical, actionable guidance on the mechanics and implementation of AI applications in medicine. Shares career guidance on a successful future in AI in medicine. Teaches the skills to evaluate AI tools and avoid being misled by the hype. For a wide audience of healthcare professionals impacted by Artificial Intelligence in medicine, including physician-scientists, AI developers, entrepreneurs, and healthcare leaders who need to evaluate AI applications designed to improve safety, quality, and value for their institutions. Enrich Your eBook Reading Experience Read directly on your preferred device(s), such as computer, tablet, or smartphone. Easily convert to audiobook, powering your content with natural language text-to-speech.

The working conference dealt with recent developments in the field of modelling and optimization and with knowledge based decision support systems. This contributed to the realiza- tion of the aims of the working group 7.6 which are: - to promote theoretical research in the field of optimization including mathematical programming and optimal control; -to encourage the development of sophisticated knowledge based systems in which refined optimization models and algorithms are used; - to contribute to the exchange and dissemination of information and collective experience among the inter- ested groups and individuals; - to support the practical ap- plication of such systems in control, engineering, industry, economy etc. A selection of papers is included into this proceedings vo- lume since they reflect the current state of research in areas of interest to the field of (KB)DDS, and/or they are the value for the dissemination and exchange of information related to research topicsof interest, and/or they describe relevant practical experience related to designing, buil- ding, implementing and using (KB)DSS.

The Database and Expert Systems Applications - DEXA - conferences are dedi cated to providing an international forum for the presentation of applications in the database and expert systems field, for the exchange of ideas and experiences, and for defining requirements for the future systems in these fields. After the very promising DEXA 90 in Vienna, Austria, we hope to have successfully established wjth this year's DEXA 91 a stage where scientists from diverse fields interested in application-oriented research can present and discuss their work. This year there was a total of more than 250 submitted papers from 28 different countries, in all continents. Only 98 of the papers could be accepted. The collection of papers in these proceedings offers a cross-section of the issues facing the area of databases and expert systems, i.e., topics of basic research interest on one hand and questions occurring when developing applications on the other. Major credit for the success of the conference goes to all of our colleagues who submitted papers for consideration and to those who have organized and chaired the panel sessions. Many persons contributed numerous hours to organize this conference. The names of most of them will appear on the following pages. In particular we wish to thank the Organization Committee Chairmen Johann Gordesch, A Min Tjoa, and Roland Wag ner, who also helped establishing the program. Special thanks also go to Gabriella Wagner and Anke Ruckert. Dimitris Karagiannis General Conference Chairman Contents Conference Committee."

Complex machines can fail in complex ways. Often the nature of the fault can be determined only through the interpretation of machine behavior over time. This book presents a novel approach to the representation and recognition of temporally distributed symptoms. Existing diagnostic expert systems usually operate under a set of simplifying assumptions that limit their applicability. A common assumption is that the device to be diagnosed has a static behavior, with the relation between inputs and outputs constant over time. In most realistic application domains this assumption is violated and both the normal, intended function of the device and the potential malfunctions are complex behaviors over time. This book addresses the problem of systematically treating information about fault symptoms that are spread out over periods of time. These symptoms are characterized by a specific order of events, and in the general case a single snapshot of the device state does not suffice to recognize the symptoms. Instead one has to plan a measurement sequence that consists of several observations at more than one time point. Starting with a classification of various types of dynamic faulty behavior, the author identifies temporally distributed systems (TDSs) and designs a representation language that allows TDSs to be specified in a declarative manner. The definition of a successful match of a measurement sequence against a TDS specification is operationalized as an algorithm which plans such an observation sequence based on the TDS specification. The author demonstrates that his novel solution is a generic, paradigm-independent building block for diagnostic expert systems by embedding it into the frameworks of both an associative and a model-based diagnostic system. The book will be valuable both for researchers working on applications of temporal reasoning and prospective users of technical expert systems.