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Book Logical Structures for Representation of Knowledge and Uncertainty

Download or read book Logical Structures for Representation of Knowledge and Uncertainty written by Ellen Hisdal and published by . This book was released on 2014-09-01 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Logical Structures for Representation of Knowledge and Uncertainty

Download or read book Logical Structures for Representation of Knowledge and Uncertainty written by Ellen Hisdal and published by Physica. This book was released on 2013-04-17 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is the business of science not to create laws, but to discover them. We do not originate the constitution of our own minds, greatly as it may be in our power to modify their character. And as the laws of the human intellect do not depend upon our will, so the forms of science, of (1. 1) which they constitute the basis, are in all essential regards independent of individual choice. George Boole [10, p. llJ 1. 1 Comparison with Traditional Logic The logic of this book is a probability logic built on top of a yes-no or 2-valued logic. It is divided into two parts, part I: BP Logic, and part II: M Logic. 'BP' stands for 'Bayes Postulate'. This postulate says that in the absence of knowl edge concerning a probability distribution over a universe or space one should assume 1 a uniform distribution. 2 The M logic of part II does not make use of Bayes postulate or of any other postulates or axioms. It relies exclusively on purely deductive reasoning following from the definition of probabilities. The M logic goes an important step further than the BP logic in that it can distinguish between certain types of information supply sentences which have the same representation in the BP logic as well as in traditional first order logic, although they clearly have different meanings (see example 6. 1. 2; also comments to the Paris-Rome problem of eqs. (1. 8), (1. 9) below).

Book Knowledge Representation and Reasoning Under Uncertainty

Download or read book Knowledge Representation and Reasoning Under Uncertainty written by Michael Masuch and published by Springer Science & Business Media. This book was released on 1994-06-28 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is based on the International Conference Logic at Work, held in Amsterdam, The Netherlands, in December 1992. The 14 papers in this volume are selected from 86 submissions and 8 invited contributions and are all devoted to knowledge representation and reasoning under uncertainty, which are core issues of formal artificial intelligence. Nowadays, logic is not any longer mainly associated to mathematical and philosophical problems. The term applied logic has a far wider meaning, as numerous applications of logical methods, particularly in computer science, artificial intelligence, or formal linguistics, testify. As demonstrated also in this volume, a variety of non-standard logics gained increased importance for knowledge representation and reasoning under uncertainty.

Book Knowledge Processing and Decision Making in Agent Based Systems

Download or read book Knowledge Processing and Decision Making in Agent Based Systems written by Lakhmi C Jain and published by Springer Science & Business Media. This book was released on 2009-01-17 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge processing and decision making in agent-based systems constitute the key components of intelligent machines. The contributions included in the book are: Innovations in Knowledge Processing and Decision Making in Agent-Based Systems Towards Real-World HTN Planning Agents Mobile Agent-Based System for Distributed Software Maintenance Software Agents in New Generation Networks: Towards the Automation of Telecom Processes Multi-agent Systems and Paraconsistent Knowledge An Agent-based Negotiation Platform for Collaborative Decision-Making in Construction Supply Chain An Event-Driven Algorithm for Agents at the Web A Generic Mobile Agent Framework Toward Ambient Intelligence Developing Actionable Trading Strategies Agent Uncertainty Model and Quantum Mechanics Representation Agent Transportation Layer Adaptation System Software Agents to Enable Service Composition through Negotiation Advanced Technology Towards Developing Decentralized Autonomous Flexible Manufacturing Systems

Book Uncertainty Theory

    Book Details:
  • Author : Baoding Liu
  • Publisher : Springer Science & Business Media
  • Release : 2011-11-07
  • ISBN : 3642139582
  • Pages : 350 pages

Download or read book Uncertainty Theory written by Baoding Liu and published by Springer Science & Business Media. This book was released on 2011-11-07 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, countable subadditivity, and product measure axioms. Uncertainty is any concept that satisfies the axioms of uncertainty theory. Thus uncertainty is neither randomness nor fuzziness. It is also known from some surveys that a lot of phenomena do behave like uncertainty. How do we model uncertainty? How do we use uncertainty theory? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory, including uncertain programming, uncertain risk analysis, uncertain reliability analysis, uncertain process, uncertain calculus, uncertain differential equation, uncertain logic, uncertain entailment, and uncertain inference. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, system science, industrial engineering, computer science, artificial intelligence, finance, control, and management science will find this work a stimulating and useful reference.

Book Geometry of Knowledge for Intelligent Systems

Download or read book Geometry of Knowledge for Intelligent Systems written by Germano Resconi and published by Springer. This book was released on 2012-07-27 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is on the geometry of agent knowledge. The important concept studied in this book is the Field and its Geometric Representation. To develop a geometric image of the gravity , Einstein used Tensor Calculus but this is very different from the knowledge instruments used now, as for instance techniques of data mining , neural networks , formal concept analysis ,quantum computer and other topics. The aim of this book is to rebuild the tensor calculus in order to give a geometric representation of agent knowledge. By using a new geometry of knowledge we can unify all the topics that have been studied in recent years to create a bridge between the geometric representation of the physical phenomena and the geometric representation of the individual and subjective knowledge of the agents.

Book Knowledge Representation and Reasoning Under Uncertainty

Download or read book Knowledge Representation and Reasoning Under Uncertainty written by Michael Masuch and published by . This book was released on 1994 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Agent and Multi Agent Systems  Technologies and Applications

Download or read book Agent and Multi Agent Systems Technologies and Applications written by Ngoc Thanh Nguyen and published by Springer Science & Business Media. This book was released on 2007-05-24 with total page 1065 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Symposium on Agent and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2007, held in Wroclaw, Poland in May/June 2007. Coverage includes agent-oriented Web applications, mobility aspects of agent systems, agents for network management, agent approaches to robotic systems, as well as intelligent and secure agents for digital content management.

Book Conceptual Structures  Knowledge Representations as Interlingua

Download or read book Conceptual Structures Knowledge Representations as Interlingua written by Peter W. Eklund and published by Springer Science & Business Media. This book was released on 1996-07-30 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the Fourth International Conference on Conceptual Structures, ICCS '96, held in Sydney, Australia, in August 1996. The book presents five full papers by the invited speakers together with 15 revised full papers selected for presentation at the conference from a respectable number of submissions. The issues addressed are natural language processing, information retrieval, graph operations, conceptual graph and Peirce theory, knowledge acquisition, theorem proving and CG programming, and order-based organisation and encoding.

Book Quantified Representation of Uncertainty and Imprecision

Download or read book Quantified Representation of Uncertainty and Imprecision written by Dov M. Gabbay and published by Springer Science & Business Media. This book was released on 1998-10-31 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are happy to present the first volume of the Handbook of Defeasible Reasoning and Uncertainty Management Systems. Uncertainty pervades the real world and must therefore be addressed by every system that attempts to represent reality. The representation of uncertainty is a ma jor concern of philosophers, logicians, artificial intelligence researchers and com puter sciencists, psychologists, statisticians, economists and engineers. The present Handbook volumes provide frontline coverage of this area. This Handbook was produced in the style of previous handbook series like the Handbook of Philosoph ical Logic, the Handbook of Logic in Computer Science, the Handbook of Logic in Artificial Intelligence and Logic Programming, and can be seen as a companion to them in covering the wide applications of logic and reasoning. We hope it will answer the needs for adequate representations of uncertainty. This Handbook series grew out of the ESPRIT Basic Research Project DRUMS II, where the acronym is made out of the Handbook series title. This project was financially supported by the European Union and regroups 20 major European research teams working in the general domain of uncertainty. As a fringe benefit of the DRUMS project, the research community was able to create this Hand book series, relying on the DRUMS participants as the core of the authors for the Handbook together with external international experts.

Book Knowledge Representation and Reasoning Under Uncertainty

Download or read book Knowledge Representation and Reasoning Under Uncertainty written by Michael Masuch and published by . This book was released on 1994 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Expert Systems

    Book Details:
  • Author : Ian Graham
  • Publisher : Chapman & Hall
  • Release : 1988
  • ISBN :
  • Pages : 394 pages

Download or read book Expert Systems written by Ian Graham and published by Chapman & Hall. This book was released on 1988 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: A review of the present state of knowledge engineering, drawing together underlying theory from related disciplines, with particular attention to fuzzy logics, the theory of fuzzy sets, and decision support systems, along with practical applications. For managers wishing to evaluate expert decision systems, for systems designers and knowledge engineers, and for advanced undergraduate and graduate students in computer science. Many charts, diagrams, tables, and logical or mathematical formulas; extensive references. Annotation copyrighted by Book News, Inc., Portland, OR

Book Information Retrieval  Uncertainty and Logics

Download or read book Information Retrieval Uncertainty and Logics written by Cornelis Joost van Rijsbergen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, there have been several attempts to define a logic for information retrieval (IR). The aim was to provide a rich and uniform representation of information and its semantics with the goal of improving retrieval effectiveness. The basis of a logical model for IR is the assumption that queries and documents can be represented effectively by logical formulae. To retrieve a document, an IR system has to infer the formula representing the query from the formula representing the document. This logical interpretation of query and document emphasizes that relevance in IR is an inference process. The use of logic to build IR models enables one to obtain models that are more general than earlier well-known IR models. Indeed, some logical models are able to represent within a uniform framework various features of IR systems such as hypermedia links, multimedia data, and user's knowledge. Logic also provides a common approach to the integration of IR systems with logical database systems. Finally, logic makes it possible to reason about an IR model and its properties. This latter possibility is becoming increasingly more important since conventional evaluation methods, although good indicators of the effectiveness of IR systems, often give results which cannot be predicted, or for that matter satisfactorily explained. However, logic by itself cannot fully model IR. The success or the failure of the inference of the query formula from the document formula is not enough to model relevance in IR. It is necessary to take into account the uncertainty inherent in such an inference process. In 1986, Van Rijsbergen proposed the uncertainty logical principle to model relevance as an uncertain inference process. When proposing the principle, Van Rijsbergen was not specific about which logic and which uncertainty theory to use. As a consequence, various logics and uncertainty theories have been proposed and investigated. The choice of an appropriate logic and uncertainty mechanism has been a main research theme in logical IR modeling leading to a number of logical IR models over the years. Information Retrieval: Uncertainty and Logics contains a collection of exciting papers proposing, developing and implementing logical IR models. This book is appropriate for use as a text for a graduate-level course on Information Retrieval or Database Systems, and as a reference for researchers and practitioners in industry.

Book Probabilistic Logic Networks

Download or read book Probabilistic Logic Networks written by Ben Goertzel and published by Springer Science & Business Media. This book was released on 2008-12-16 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract In this chapter we provide an overview of probabilistic logic networks (PLN), including our motivations for developing PLN and the guiding principles underlying PLN. We discuss foundational choices we made, introduce PLN knowledge representation, and briefly introduce inference rules and truth-values. We also place PLN in context with other approaches to uncertain inference. 1.1 Motivations This book presents Probabilistic Logic Networks (PLN), a systematic and pragmatic framework for computationally carrying out uncertain reasoning – r- soning about uncertain data, and/or reasoning involving uncertain conclusions. We begin with a few comments about why we believe this is such an interesting and important domain of investigation. First of all, we hold to a philosophical perspective in which “reasoning” – properly understood – plays a central role in cognitive activity. We realize that other perspectives exist; in particular, logical reasoning is sometimes construed as a special kind of cognition that humans carry out only occasionally, as a deviation from their usual (intuitive, emotional, pragmatic, sensorimotor, etc.) modes of thought. However, we consider this alternative view to be valid only according to a very limited definition of “logic.” Construed properly, we suggest, logical reasoning may be understood as the basic framework underlying all forms of cognition, including those conventionally thought of as illogical and irrational.

Book Computer Aided Materials Selection During Structural Design

Download or read book Computer Aided Materials Selection During Structural Design written by National Research Council and published by National Academies Press. This book was released on 1995-04-03 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: The selection of the proper materials for a structural component is a critical activity that is governed by many, often conflicting factors. Incorporating materials expert systems into CAD/CAM operations could assist designers by suggesting potential manufacturing processes for particular products to facilitate concurrent engineering, recommending various materials for a specific part based on a given set of characteristics, or proposing possible modifications of a design if suitable materials for a particular part do not exist. This book reviews the structural design process, determines the elements, and capabilities required for a materials selection expert system to assist design engineers, and recommends the areas of expert system and materials modeling research and development required to devise a materials-specific design system.

Book Lees  Loss Prevention in the Process Industries

Download or read book Lees Loss Prevention in the Process Industries written by Frank Lees and published by Butterworth-Heinemann. This book was released on 2005-01-10 with total page 3708 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last three decades the process industries have grown very rapidly, with corresponding increases in the quantities of hazardous materials in process, storage or transport. Plants have become larger and are often situated in or close to densely populated areas. Increased hazard of loss of life or property is continually highlighted with incidents such as Flixborough, Bhopal, Chernobyl, Three Mile Island, the Phillips 66 incident, and Piper Alpha to name but a few. The field of Loss Prevention is, and continues to, be of supreme importance to countless companies, municipalities and governments around the world, because of the trend for processing plants to become larger and often be situated in or close to densely populated areas, thus increasing the hazard of loss of life or property. This book is a detailed guidebook to defending against these, and many other, hazards. It could without exaggeration be referred to as the "bible" for the process industries. This is THE standard reference work for chemical and process engineering safety professionals. For years, it has been the most complete collection of information on the theory, practice, design elements, equipment, regulations and laws covering the field of process safety. An entire library of alternative books (and cross-referencing systems) would be needed to replace or improve upon it, but everything of importance to safety professionals, engineers and managers can be found in this all-encompassing reference instead. Frank Lees' world renowned work has been fully revised and expanded by a team of leading chemical and process engineers working under the guidance of one of the world's chief experts in this field. Sam Mannan is professor of chemical engineering at Texas A&M University, and heads the Mary Kay O'Connor Process Safety Center at Texas A&M. He received his MS and Ph.D. in chemical engineering from the University of Oklahoma, and joined the chemical engineering department at Texas A&M University as a professor in 1997. He has over 20 years of experience as an engineer, working both in industry and academia. New detail is added to chapters on fire safety, engineering, explosion hazards, analysis and suppression, and new appendices feature more recent disasters. The many thousands of references have been updated along with standards and codes of practice issued by authorities in the US, UK/Europe and internationally. In addition to all this, more regulatory relevance and case studies have been included in this edition. Written in a clear and concise style, Loss Prevention in the Process Industries covers traditional areas of personal safety as well as the more technological aspects and thus provides balanced and in-depth coverage of the whole field of safety and loss prevention. * A must-have standard reference for chemical and process engineering safety professionals * The most complete collection of information on the theory, practice, design elements, equipment and laws that pertain to process safety * Only single work to provide everything; principles, practice, codes, standards, data and references needed by those practicing in the field

Book Handbook of Defeasible Reasoning and Uncertainty Management Systems

Download or read book Handbook of Defeasible Reasoning and Uncertainty Management Systems written by Dov M. Gabbay and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reasoning under uncertainty is always based on a specified language or for malism, including its particular syntax and semantics, but also on its associated inference mechanism. In the present volume of the handbook the last aspect, the algorithmic aspects of uncertainty calculi are presented. Theory has suffi ciently advanced to unfold some generally applicable fundamental structures and methods. On the other hand, particular features of specific formalisms and ap proaches to uncertainty of course still influence strongly the computational meth ods to be used. Both general as well as specific methods are included in this volume. Broadly speaking, symbolic or logical approaches to uncertainty and nu merical approaches are often distinguished. Although this distinction is somewhat misleading, it is used as a means to structure the present volume. This is even to some degree reflected in the two first chapters, which treat fundamental, general methods of computation in systems designed to represent uncertainty. It has been noted early by Shenoy and Shafer, that computations in different domains have an underlying common structure. Essentially pieces of knowledge or information are to be combined together and then focused on some particular question or domain. This can be captured in an algebraic structure called valuation algebra which is described in the first chapter. Here the basic operations of combination and focus ing (marginalization) of knowledge and information is modeled abstractly subject to simple axioms.