General game players are computer systems able to play strategy games based solely on formal game descriptions supplied at "runtime" (n other words, they don't know the rules until the game starts). Unlike specialized game players, such as Deep Blue, general game players cannot rely on algorithms designed in advance for specific games; they must discover such algorithms themselves. General game playing expertise depends on intelligence on the part of the game player and not just intelligence of the programmer of the game player. GGP is an interesting application in its own right. It is intellectually engaging and more than a little fun. But it is much more than that. It provides a theoretical framework for modeling discrete dynamic systems and defining rationality in a way that takes into account problem representation and complexities like incompleteness of information and resource bounds. It has practical applications in areas where these features are important, e.g., in business and law. More fundamentally, it raises questions about the nature of intelligence and serves as a laboratory in which to evaluate competing approaches to artificial intelligence. This book is an elementary introduction to General Game Playing (GGP). (1) It presents the theory of General Game Playing and leading GGP technologies. (2) It shows how to create GGP programs capable of competing against other programs and humans. (3) It offers a glimpse of some of the real-world applications of General Game Playing.
Data integration is a critical problem in our increasingly interconnected but inevitably heterogeneous world. There are numerous data sources available in organizational databases and on public information systems like the World Wide Web. Not surprisingly, the sources often use different vocabularies and different data structures, being created, as they are, by different people, at different times, for different purposes. The goal of data integration is to provide programmatic and human users with integrated access to multiple, heterogeneous data sources, giving each user the illusion of a single, homogeneous database designed for his or her specific need. The good news is that, in many cases, the data integration process can be automated. This book is an introduction to the problem of data integration and a rigorous account of one of the leading approaches to solving this problem, viz., the relational logic approach. Relational logic provides a theoretical framework for discussing data integration. Moreover, in many important cases, it provides algorithms for solving the problem in a computationally practical way. In many respects, relational logic does for data integration what relational algebra did for database theory several decades ago. A companion web site provides interactive demonstrations of the algorithms. Table of Contents: Preface / Interactive Edition / Introduction / Basic Concepts / Query Folding / Query Planning / Master Schema Management / Appendix / References / Index / Author Biography Don't have access? Recommend our Synthesis Digital Library to your library or purchase a personal subscription. Email info@morganclaypool.com for details.
Logic Programming is a style of programming in which programs take the form of sets of sentences in the language of Symbolic Logic. Over the years, there has been growing interest in Logic Programming due to applications in deductive databases, automated worksheets, Enterprise Management (business rules), Computational Law, and General Game Playing. This book introduces Logic Programming theory, current technology, and popular applications. In this volume, we take an innovative, model-theoretic approach to logic programming. We begin with the fundamental notion of datasets, i.e., sets of ground atoms. Given this fundamental notion, we introduce views, i.e., virtual relations; and we define classical logic programs as sets of view definitions, written using traditional Prolog-like notation but with semantics given in terms of datasets rather than implementation. We then introduce actions, i.e., additions and deletions of ground atoms; and we define dynamic logic programs as sets of action definitions. In addition to the printed book, there is an online version of the text with an interpreter and a compiler for the language used in the text and an integrated development environment for use in developing and deploying practical logic programs. "This is a book for the 21st century: presenting an elegant and innovative perspective on logic programming. Unlike other texts, it takes datasets as a fundamental notion, thereby bridging the gap between programming languages and knowledge representation languages; and it treats updates on an equal footing with datasets, leading to a sound and practical treatment of action and change." - Bob Kowalski, Professor Emeritus, Imperial College London "In a world where Deep Learning and Python are the talk of the day, this book is a remarkable development. It introduces the reader to the fundamentals of traditional Logic Programming and makes clear the benefits of using the technology to create runnable specifications for complex systems." - Son Cao Tran, Professor in Computer Science, New Mexico State University "Excellent introduction to the fundamentals of Logic Programming. The book is well-written and well-structured. Concepts are explained clearly and the gradually increasing complexity of exercises makes it so that one can understand easy notions quickly before moving on to more difficult ideas." - George Younger, student, Stanford University
This book is a gentle but rigorous introduction to Formal Logic. It is intended primarily for use at the college level. However, it can also be used for advanced secondary school students, and it can be used at the start of graduate school for those who have not yet seen the material. The approach to teaching logic used here emerged from more than 20 years of teaching logic to students at Stanford University and from teaching logic to tens of thousands of others via online courses on the World Wide Web. The approach differs from that taken by other books in logic in two essential ways, one having to do with content, the other with form. Like many other books on logic, this one covers logical syntax and semantics and proof theory plus induction. However, unlike other books, this book begins with Herbrand semantics rather than the more traditional Tarskian semantics. This approach makes the material considerably easier for students to understand and leaves them with a deeper understanding of what logic is all about. In addition to this text, there are online exercises (with automated grading), online logic tools and applications, online videos of lectures, and an online forum for discussion. They are available at logic.stanford.edu/intrologic/
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 book is a gentle but rigorous introduction to Formal Logic. It is intended primarily for use at the college level. However, it can also be used for advanced secondary school students, and it can be used at the start of graduate school for those who have not yet seen the material. The approach to teaching logic used here emerged from more than 20 years of teaching logic to students at Stanford University and from teaching logic to tens of thousands of others via online courses on the World Wide Web. The approach differs from that taken by other books in logic in two essential ways, one having to do with content, the other with form. Like many other books on logic, this one covers logical syntax and semantics and proof theory plus induction. However, unlike other books, this book begins with Herbrand semantics rather than the more traditional Tarskian semantics. This approach makes the material considerably easier for students to understand and leaves them with a deeper understanding of what logic is all about. In addition to this text, there are online exercises (with automated grading), online logic tools and applications, online videos of lectures, and an online forum for discussion. They are available at http://intrologic.stanford.edu/
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.
Mark d'Inverno and Michael Luck present a formal approach to dealing with agents and agent systems in this second edition of Understanding Agent Systems. The Z specification language is used to establish an accessible and unified formal account of agent systems and inter-agent relationships. In particular, the framework provides precise and unambiguous meanings for common concepts and terms for agent systems, allows for the description of alternative agent models and architectures, and serves as a foundation for subsequent development of increasingly refined agent concepts. The practicability of this approach is verified by applying the formal framework to three detailed case studies. The book will appeal equally to researchers, students, and professionals in industry.
The study of multi-agent systems (MAS) focuses on systems in which many intelligent agents interact with each other. These agents are considered to be autonomous entities such as software programs or robots. Their interactions can either be cooperative (for example as in an ant colony) or selfish (as in a free market economy). This book assumes only basic knowledge of algorithms and discrete maths, both of which are taught as standard in the first or second year of computer science degree programmes. A basic knowledge of artificial intelligence would useful to help understand some of the issues, but is not essential. The book’s main aims are: To introduce the student to the concept of agents and multi-agent systems, and the main applications for which they are appropriate To introduce the main issues surrounding the design of intelligent agents To introduce the main issues surrounding the design of a multi-agent society To introduce a number of typical applications for agent technology After reading the book the student should understand: The notion of an agent, how agents are distinct from other software paradigms (e.g. objects) and the characteristics of applications that lend themselves to agent-oriented software The key issues associated with constructing agents capable of intelligent autonomous action and the main approaches taken to developing such agents The key issues in designing societies of agents that can effectively cooperate in order to solve problems, including an understanding of the key types of multi-agent interactions possible in such systems The main application areas of agent-based systems
This is the updated new edition from the founder and inventor of the subject. It provides an account of the principles and a survey of modelling in hydraulic, coastal and offshore engineering.
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 develops allocation mechanisms that aim to ensure an efficient resource allocation in modern IT-services. Recent methods of artificial intelligence, such as neural networks and reinforcement learning, and nature-oriented optimization methods, such as genetic algorithms and simulated annealing, are advanced and applied to allocation processes in distributed IT-infrastructures, or grid systems.
Distributed Artificial Intelligence presents a collection of papers describing the state of research in distributed artificial intelligence (DAI). DAI is concerned with the cooperative solution of problems by a decentralized group of agents. The agents may range from simple processing elements to complex entities exhibiting rational behavior. The book is organized into three parts. Part I addresses ways to develop control abstractions that efficiently guide problem-solving; communication abstractions that yield cooperation; and description abstractions that result in effective organizational structure. Part II describes architectures for developing and testing DAI systems. Part III discusses applications of DAI in manufacturing, office automation, and man-machine interactions. This book is intended for researchers, system developers, and students in artificial intelligence and related disciplines. It can also be used as a reference for students and researchers in other disciplines, such as psychology, philosophy, robotics, and distributed computing, who wish to understand the issues of DAI.
Autonomous, Model-Based Diagnosis Agents defines and describes the implementation of an architecture for autonomous, model-based diagnosis agents. It does this by developing a logic programming approach for model-based diagnosis and introducing strategies to deal with more complex diagnosis problems, and then embedding the diagnosis framework into the agent architecture of vivid agents. Autonomous, Model-Based Diagnosis Agents surveys extended logic programming and shows how this expressive language is used to model diagnosis problems stemming from applications such as digital circuits, traffic control, integrity checking of a chemical database, alarm-correlation in cellular phone networks, diagnosis of an automatic mirror furnace, and diagnosis of communication protocols. The book reviews a bottom-up algorithm to remove contradiction from extended logic programs and substantially improves it by top-down evaluation of extended logic programs. Both algorithms are evaluated in the circuit domain including some of the ISCAS85 benchmark circuits. This comprehensive in-depth study of concepts, architectures, and implementation of autonomous, model-based diagnosis agents will be of great value for researchers, engineers, and graduate students with a background in artificial intelligence. For practitioners, it provides three main contributions: first, it provides many examples from diverse areas such as alarm correlation in phone networks to inconsistency checking in databases; second, it describes an architecture to develop agents; and third, it describes a sophisticated and declarative implementation of the concepts and architectures introduced.
This text presents a reflective theory of school didactics, incorporating German and Nordic research traditions in the theory of didactics, together with Anglo-American research on teaching instructional research and cognitivist theory.
Automated trading in electronic markets is one of the most common and consequential applications of autonomous software agents. Design of effective trading strategies requires thorough understanding of how market mechanisms operate, and appreciation of strategic issues that commonly manifest in trading scenarios. Drawing on research in auction theory and artificial intelligence, this book presents core principles of strategic reasoning that apply to market situations. The author illustrates trading strategy choices through examples of concrete market environments, such as eBay, as well as abstract market models defined by configurations of auctions and traders. Techniques for addressing these choices constitute essential building blocks for the design of trading strategies for rich market applications.The lecture assumes no prior background in game theory or auction theory, or artificial intelligence.Table of Contents: Introduction / Example: Bidding on eBay / Auction Fundamentals / Continuous Double Auctions / Interdependent Markets / Conclusion
An argument for a non-Cartesian philosophical foundation for cognitive science that combines elements of Heideggerian phenomenology, a dynamical systems approach to cognition, and insights from artificial intelligence-related robotics.
Intelligent agents are computer systems that are capable of flexible autonomous action in dynamic, typically multi-agent domains. Over the past few years, the computer science community has begun to recognise that the technology of intelligent agents provides the key to solving a range of complex software application problems, for which traditional software engineering tools and techniques offer no solution. This book, the third in a series, represents the state of the art in the science of agent systems. It is based on papers presented at the 3rd workshop on Agent Theories, Architectures and Languages (ATAL'96), held in conjunction with the European Conference on Artificial Intelligence (ECAI'96) in Budapest, Hungary, in August 1996. It is essential reading for anyone interested in this vital new technology.
Artificial systems that think and behave intelligently are one of the most exciting and challenging goals of Artificial Intelligence. Action Programming is the art and science of devising high-level control strategies for autonomous systems which employ a mental model of their environment and which reason about their actions as a means to achieve their goals. Applications of this programming paradigm include autonomous software agents, mobile robots with high-level reasoning capabilities, and General Game Playing. These lecture notes give an in-depth introduction to the current state-of-the-art in action programming. The main topics are knowledge representation for actions, procedural action programming, planning, agent logic programs, and reactive, behavior-based agents. The only prerequisite for understanding the material in these lecture notes is some general programming experience and basic knowledge of classical first-order logic. Table of Contents: Introduction / Mathematical Preliminaries / Procedural Action Programs / Action Programs and Planning / Declarative Action Programs / Reactive Action Programs / Suggested Further Reading
The Truth Maintenance Workshop was held in August 1990 during the European Conference on Artificial Intelligence in Stockholm, Sweden. Ten selected papers, eight of them presented at the workshop, are included in this volume. The papers can be grouped into four main areas: - Meta-level control: the goal here is to specify some meta-criteria to control the behavior of the TMS. - Extensions of TMS: here the aim is to incorporate new mechanisms into TMS-like systems. - Foundations: there is now much interest in providing formal descriptions of TMS, proving results about them, and relating them with other non-monotonic formalisms. - Belief revision: TMS can be considered as providing support to manage the more general problem of belief revision.
This book focuses on the belief-desire-intention (BDI) model of rational agents, which recognizes the primacy of beliefs, desires, and intentions in rational action. One goal of modern computer science is to engineer computer programs that can act as autonomous, rational agents; software that can independently make good decisions about what actions to perform on our behalf and execute those actions. Applications range from small programs that intelligently search the Web buying and selling goods via electronic commerce, to autonomous space probes. This book focuses on the belief-desire-intention (BDI) model of rational agents, which recognizes the primacy of beliefs, desires, and intentions in rational action. The BDI model has three distinct strengths: an underlying philosophy based on practical reasoning in humans, a software architecture that is implementable in real systems, and a family of logics that support a formal theory of rational agency.The book introduces a BDI logic called LORA (Logic of Rational Agents). In addition to the BDI component, LORA contains a temporal component, which allows one to represent the dynamics of how agents and their environments change over time, and an action component, which allows one to represent the actions that agents perform and the effects of the actions. The book shows how LORA can be used to capture many components of a theory of rational agency, including such notions as communication and cooperation.
From the reviews: "Bishop and Schroder (both, Univ. of Nebraska at Omaha) have brought together an impressive group of practitioners in the relatively new application of geographic information science to mountain geomorphology. In doing so, they have produced valuable, first, overall coverage of a high-tech approach to mountain, three-dimensional research. More than 40 contributing authors discuss a wide range of related aspects.... The book is well bound and well produced; each chapter provides an extensive source of references. The numerous line drawings are clearly reproduced, although the mediocre quality of photographic reproduction limits the value of air photographs and satellite images. As is characteristic of many edited collections, there is some variation in chapter quality. Some of the writing is so dense that it requires minute concentration--one chapter, for instance, has 14 pages of references from a total of 43 pages. Nevertheless, this is a vital compendium for a rapidly expanding field of research. Summing Up: Recommended. Upper-division undergraduates through professionals." (J. D. Ives, Choice, March 2005)
Part of the International Series in Mathematics Mathematical Modeling for the Scientific Method is intended for the sophomore/junior-level student seeking to be well-grounded in mathematical modeling for their studies in biology, the physical sciences, engineering, and/or medicine. It clarifies the connection between deductive and inductive reasoning as used in Mathematics and Science and urges students to think critically about concepts and applications. The authors’ goal is to be introductory in level while covering a broad range of techniques. They unite topics in statistics, linear algebra, calculus and differential equations, while discussing how these subjects are interrelated and utilized. Mathematical Modeling for the Scientific Method leaves students with a clearer perspective of the role of mathematics within the sciences and the understanding of how to rationally work through even rigorous applications with ease.
Cooperative game theory is a branch of (micro-)economics that studies the behavior of self-interested agents in strategic settings where binding agreements among agents are possible. Our aim in this book is to present a survey of work on the computational aspects of cooperative game theory. We begin by formally defining transferable utility games in characteristic function form, and introducing key solution concepts such as the core and the Shapley value. We then discuss two major issues that arise when considering such games from a computational perspective: identifying compact representations for games, and the closely related problem of efficiently computing solution concepts for games. We survey several formalisms for cooperative games that have been proposed in the literature, including, for example, cooperative games defined on networks, as well as general compact representation schemes such as MC-nets and skill games. As a detailed case study, we consider weighted voting games: a widely-used and practically important class of cooperative games that inherently have a natural compact representation. We investigate the complexity of solution concepts for such games, and generalizations of them. We briefly discuss games with non-transferable utility and partition function games. We then overview algorithms for identifying welfare-maximizing coalition structures and methods used by rational agents to form coalitions (even under uncertainty), including bargaining algorithms. We conclude by considering some developing topics, applications, and future research directions.
Automated trading in electronic markets is one of the most common and consequential applications of autonomous software agents. Design of effective trading strategies requires thorough understanding of how market mechanisms operate, and appreciation of strategic issues that commonly manifest in trading scenarios. Drawing on research in auction theory and artificial intelligence, this book presents core principles of strategic reasoning that apply to market situations. The author illustrates trading strategy choices through examples of concrete market environments, such as eBay, as well as abstract market models defined by configurations of auctions and traders. Techniques for addressing these choices constitute essential building blocks for the design of trading strategies for rich market applications. The lecture assumes no prior background in game theory or auction theory, or artificial intelligence. Table of Contents: Introduction / Example: Bidding on eBay / Auction Fundamentals / Continuous Double Auctions / Interdependent Markets / Conclusion
The name "temporal logic" may sound complex and daunting; but while they describe potentially complex scenarios, temporal logics are often based on a few simple, and fundamental, concepts - highlighted in this book. An Introduction to Practical Formal Methods Using Temporal Logic provides an introduction to formal methods based on temporal logic, for developing and testing complex computational systems. These methods are supported by many well-developed tools, techniques and results that can be applied to a wide range of systems. Fisher begins with a full introduction to the subject, covering the basics of temporal logic and using a variety of examples, exercises and pointers to more advanced work to help clarify and illustrate the topics discussed. He goes on to describe how this logic can be used to specify a variety of computational systems, looking at issues of linking specifications, concurrency, communication and composition ability. He then analyses temporal specification techniques such as deductive verification, algorithmic verification, and direct execution to develop and verify computational systems. The final chapter on case studies analyses the potential problems that can occur in a range of engineering applications in the areas of robotics, railway signalling, hardware design, ubiquitous computing, intelligent agents, and information security, and explains how temporal logic can improve their accuracy and reliability. Models temporal notions and uses them to analyze computational systems Provides a broad approach to temporal logic across many formal methods - including specification, verification and implementation Introduces and explains freely available tools based on temporal logics and shows how these can be applied Presents exercises and pointers to further study in each chapter, as well as an accompanying website providing links to additional systems based upon temporal logic as well as additional material related to the book.
Jason is an Open Source interpreter for an extended version of AgentSpeak – a logic-based agent-oriented programming language – written in JavaTM. It enables users to build complex multi-agent systems that are capable of operating in environments previously considered too unpredictable for computers to handle. Jason is easily customisable and is suitable for the implementation of reactive planning systems according to the Belief-Desire-Intention (BDI) architecture. Programming Multi-Agent Systems in AgentSpeak using Jason provides a brief introduction to multi-agent systems and the BDI agent architecture on which AgentSpeak is based. The authors explain Jason’s AgentSpeak variant and provide a comprehensive, practical guide to using Jason to program multi-agent systems. Some of the examples include diagrams generated using an agent-oriented software engineering methodology particularly suited for implementation using BDI-based programming languages. The authors also give guidance on good programming style with AgentSpeak. Programming Multi-Agent Systems in AgentSpeak using Jason Describes and explains in detail the AgentSpeak extension interpreted by Jason and shows how to create multi-agent systems using the Jason platform. Reinforces learning with examples, problems, and illustrations. Includes two case studies which demonstrate the use of Jason in practice. Features an accompanying website that provides further learning resources including sample code, exercises, and slides This essential guide to AgentSpeak and Jason will be invaluable to senior undergraduate and postgraduate students studying multi-agent systems. The book will also be of interest to software engineers, designers, developers, and programmers interested in multi-agent systems.
Proceedings of Es2000, the Twentieth Sges International Conference on Knowledge Based Systems and Applied Artificial Intelligence, Cambridge, December 2000
Proceedings of Es2000, the Twentieth Sges International Conference on Knowledge Based Systems and Applied Artificial Intelligence, Cambridge, December 2000
The papers in this volume are the Applications papers presented at ES 2000, the Twentieth SGES International Conference on Knowledge Based Systems and Applied Artificial Intelligence, held in Cambridge in December 2000. The scope of the Application papers has expanded over recent years to cover not just innovative applications using traditional knowledge based systems, but also to include applications demonstrating the whole range of AI technologies. These papers continue to illustrate the maturity of AI as a commercially viable technology to solve real world problems. This is the eighth volume in the Applications and Innovations in Intelligent Systems series. The series serves as a key reference as to how AI technology has enabled organisations to solve complex problems and gain significant business benefits. The Technical Stream papers from ES 200 are published as a companion volume under the title Research and Development in Intelligent Systems XVII.
Even simple agents, such as LEGO robots, are capable of exhibiting complex behaviour when they can sense and alter the world around them. From Bricks to Brains offers an introduction to embodied cognitive science and illustrates its foundational ideas through the construction and observation of LEGO Mindstorms robots. Discussing the characteristics that distinguish embodied cognitive science from classical cognitive science, the authors place a renewed emphasis on sensing and acting, on the importance of physical embodiment, and on the exploration of distributed notions of control. They also show how synthesizing simple systems and observing their behaviour can generate new theoretical insights. Numerous examples are brought forward to illustrate a key theme: the importance of environment to an actor. Even simple agents, such as LEGO robots, are capable of exhibiting complex behaviour when they can sense and alter the world around them.
Inhaltsangabe:Abstract: At present, the World Wide Web faces several problems regarding the search for specific in formation, arising, on the one hand, from the vast number of information sources available, and, on the other hand, from their intrinsic heterogeneity. A promising approach for solving the complex problems emerging in this context is the use of information agents in a multi-agent environment, which cooperatively solve advanced information-retrieval problems. An intelligent information agent provides advanced capabilities resorting to some form of logical reasoning, based on ad-hoc-knowledge about the task in question and on background knowledge of the domain, suitably represented in a knowledge base. In this thesis, our interest is in the role which some methods from the field of declarative logic programming can play in the realization of reasoning capabilities for intelligent information agents. We consider the task of updating extended logic programs (ELPs), since, in order to ensure adaptivity, an agent s knowledge base is subject to change. To this end, we develop update agents, which follow a declarative update policy and a reimplemented in the IMPACT agent environment. The proposed update agents adhere to a clear semantics and are able to deal with incomplete or in consistent information in an appropriate way. Furthermore, we introduce a framework for reasoning about evolving knowledgebases, which are represented as ELPs and maintained by an update policy. We describe a formal model which captures various update approaches, and define a logical language for expressing properties of evolving knowledge bases. We further investigate these mantical properties of knowledge states with respect to reasoning. In particular, we describe finitary characterizations of the knowledge evolution, and derive complexity results for our framework. Finally, we consider aparticular problem of information agents, namely information source selection, and develop an intelligent site-selection agent. We use ELPs for representing relevant knowledge and for declarative query an alysis and query abstraction. We define syntax and semantics of declarative site-selection programs, making use of advanced methods from answer set programming for priority handling and quantitative reasoning. A site selection component is implemented on top of the DLVKR system and its plp front-end for prioritized ELPs. We report experimental results for this implementation, [...]
Service-oriented computing is an emerging factor in IT research and development. Organizations like W3C and the EU have begun research projects to develop industrial-strength applications. This book offers a thorough, practical introduction to one of the most promising approaches – the Web Service Modeling Ontology (WSMO). After a brief review of technologies and standards of the Worldwide Web, the Semantic Web, and Web Services, the book examines WSMO from the fundamentals to applications in e-commerce, e-government and e-banking; it also describes its relation to OWL-S and WSDL-S and other applications. The book offers an up-to-date introduction, plus pointers to future applications.
Query reformulation refers to a process of translating a source query—a request for information in some high-level logic-based language—into a target plan that abides by certain interface restrictions. Many practical problems in data management can be seen as instances of the reformulation problem. For example, the problem of translating an SQL query written over a set of base tables into another query written over a set of views; the problem of implementing a query via translating to a program calling a set of database APIs; the problem of implementing a query using a collection of web services. In this book we approach query reformulation in a very general setting that encompasses all the problems above, by relating it to a line of research within mathematical logic. For many decades logicians have looked at the problem of converting "implicit definitions" into "explicit definitions," using an approach known as interpolation. We will review the theory of interpolation, and explain its close connection with query reformulation. We will give a detailed look at how the interpolation-based approach is used to generate translations between logic-based queries over different vocabularies, and also how it can be used to go from logic-based queries to programs.
If one were forced to use a single key word to describe the decade of the 1980's, a very prominent one would be "technology. " Leading the forefront of tech nology advancement were breakthroughs in electronics. Devices that were uncommon or unknown in 1980 became commonplace, and almost indispens able, by 1989. This trend has continued into the 1990's and it does not seem to be abating in any way. Microwave ovens, video recorders, telephone answer ing machines, compact disc players, computers, and a host of smaller or less sophisticated devices now appear in most households. The development of small and inexpensive computers, i. e. , personal computers, has placed computing resources within reach of many more people. In addition, many traditional, and largely mechanical devices, have been enhanced by electronics. For example, specialized microprocessors are combined with arrays of electronic sensors to control and monitor sophisticated engineering components in most new auto mobiles. In this and many other ways, we are touched by the new electronics in almost every aspect of our daily lives. Initially, personal computers were little more than toys. They contained only a small fraction of the computing power of their immediate ancestors, the mini computers and mainframe computers. However, rapid improvements in integ rated circuit design and chip manufacture produced regular reductions in size and cost of computer components. During the same time, processor speed and sophistication increased.
This book presents case-based reasoning in a systematic approach with two goals: to present rigorous and formally valid structures for precise case-based reasoning, and to demonstrate the range of techniques, methods, and tools available for many applications.
Design Automation: Automated Full-Custom VLSI Layout Using the ULYSSES Design Environment deals with the use of the Ulysses design environment for an automated full-custom VLSI layout. Topics covered include VLSI chip design and design process, control mechanisms in Ulysses, and the use of artificial intelligence (AI) in design environments. An example design task is also presented. This book is comprised of 10 chapters and begins with an overview of VLSI computer-aided design (CAD), focusing on an expert system based design environment aimed at solving the CAD tool integration problem. An example CAD tool suite for such an environment is presented. The next chapter describes prior attempts at developing an integrated design environment, followed by a discussion on the computer-aided VLSI design process that motivated the development of the Ulysses design environment. The following chapters explore the use of AI techniques within Ulysses; the fundamental architecture of Ulysses; and the control mechanisms that govern the decision to execute various CAD tools, on particular files, within Ulysses. The implementation of Ulysses is also discussed. The final chapter demonstrates the feasibility of a knowledge-based design environment for VLSI chip design applications; the success of Ulysses at further automating the VLSI design process; and the usability of Ulysses as a VLSI design environment. This monograph will be a valuable resource for systems designers and other practitioners in computer science and computer engineering.
The interaction of database and AI technologies is crucial to such applications as data mining, active databases, and knowledge-based expert systems. This volume collects the primary readings on the interactions, actual and potential, between these two fields. The editors have chosen articles to balance significant early research and the best and most comprehensive articles from the 1980s. An in-depth introduction discusses basic research motivations, giving a survey of the history, concepts, and terminology of the interaction. Major themes, approaches and results, open issues and future directions are all discussed, including the results of a major survey conducted by the editors of current work in industry and research labs. Thirteen sections follow, each with a short introduction. Topics examined include semantic data models with emphasis on conceptual modeling techniques for databases and information systems and the integration of data model concepts in high-level data languages, definition and maintenance of integrity constraints in databases and knowledge bases, natural language front ends, object-oriented database management systems, implementation issues such as concurrency control and error recovery, and representation of time and knowledge incompleteness from the viewpoints of databases, logic programming, and AI.
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