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Books in Reasoning

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1-10 of 14 results in All results

Uncertainty in Artificial Intelligence 5

  • 1st Edition
  • Volume 10
  • October 3, 2014
  • R.D. Shachter + 3 more
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 9 6 5 5 - 5
This volume, like its predecessors, reflects the cutting edge of research on the automation of reasoning under uncertainty.A more pragmatic emphasis is evident, for although some papers address fundamental issues, the majority address practical issues. Topics include the relations between alternative formalisms (including possibilistic reasoning), Dempster-Shafer belief functions, non-monotonic reasoning, Bayesian and decision theoretic schemes, and new inference techniques for belief nets. New techniques are applied to important problems in medicine, vision, robotics, and natural language understanding.

Knowledge-Based Configuration

  • 1st Edition
  • March 31, 2014
  • Alexander Felfernig + 3 more
  • English
  • eBook
    9 7 8 - 0 - 1 2 - 4 1 5 8 6 9 - 6
Knowledge-based Configuration incorporates knowledge representation formalisms to capture complex product models and reasoning methods to provide intelligent interactive behavior with the user. This book represents the first time that corporate and academic worlds collaborate integrating research and commercial benefits of knowledge-based configuration. Foundational interdisciplinary material is provided for composing models from increasingly complex products and services. Case studies, the latest research, and graphical knowledge representations that increase understanding of knowledge-based configuration provide a toolkit to continue to push the boundaries of what configurators can do and how they enable companies and customers to thrive.

Commonsense Reasoning

  • 1st Edition
  • January 19, 2006
  • Erik T. Mueller
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 4 7 6 6 1 - 2
To endow computers with common sense is one of the major long-term goals of Artificial Intelligence research. One approach to this problem is to formalize commonsense reasoning using mathematical logic. Commonsense Reasoning is a detailed, high-level reference on logic-based commonsense reasoning. It uses the event calculus, a highly powerful and usable tool for commonsense reasoning, which Erik T. Mueller demonstrates as the most effective tool for the broadest range of applications. He provides an up-to-date work promoting the use of the event calculus for commonsense reasoning, and bringing into one place information scattered across many books and papers. Mueller shares the knowledge gained in using the event calculus and extends the literature with detailed event calculus solutions to problems that span many areas of the commonsense world.

Handbook of Temporal Reasoning in Artificial Intelligence

  • 1st Edition
  • Volume 1
  • March 1, 2005
  • Michael David Fisher + 2 more
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 3 3 3 6 - 0
This collection represents the primary reference work for researchers and students in the area of Temporal Reasoning in Artificial Intelligence. Temporal reasoning has a vital role to play in many areas, particularly Artificial Intelligence. Yet, until now, there has been no single volume collecting together the breadth of work in this area. This collection brings together the leading researchers in a range of relevant areas and provides an coherent description of the breadth of activity concerning temporal reasoning in the filed of Artificial Intelligence.Key Features:- Broad range: foundations; techniques and applications- Leading researchers around the world have written the chapters- Covers many vital applications- Source book for Artificial Intelligence, temporal reasoning- Approaches provide foundation for many future software systems

Knowledge Representation and Reasoning

  • 1st Edition
  • May 19, 2004
  • Ronald Brachman + 1 more
  • English
  • Hardback
    9 7 8 - 1 - 5 5 8 6 0 - 9 3 2 - 7
  • eBook
    9 7 8 - 0 - 0 8 - 0 4 8 9 3 2 - 2
Knowledge representation is at the very core of a radical idea for understanding intelligence. Instead of trying to understand or build brains from the bottom up, its goal is to understand and build intelligent behavior from the top down, putting the focus on what an agent needs to know in order to behave intelligently, how this knowledge can be represented symbolically, and how automated reasoning procedures can make this knowledge available as needed. This landmark text takes the central concepts of knowledge representation developed over the last 50 years and illustrates them in a lucid and compelling way. Each of the various styles of representation is presented in a simple and intuitive form, and the basics of reasoning with that representation are explained in detail. This approach gives readers a solid foundation for understanding the more advanced work found in the research literature. The presentation is clear enough to be accessible to a broad audience, including researchers and practitioners in database management, information retrieval, and object-oriented systems as well as artificial intelligence. This book provides the foundation in knowledge representation and reasoning that every AI practitioner needs.

Many-Dimensional Modal Logics: Theory and Applications

  • 1st Edition
  • Volume 148
  • October 21, 2003
  • A. Kurucz + 3 more
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 3 5 7 8 - 4
Modal logics, originally conceived in philosophy, have recently found many applications in computer science, artificial intelligence, the foundations of mathematics, linguistics and other disciplines. Celebrated for their good computational behaviour, modal logics are used as effective formalisms for talking about time, space, knowledge, beliefs, actions, obligations, provability, etc. However, the nice computational properties can drastically change if we combine some of these formalisms into a many-dimensional system, say, to reason about knowledge bases developing in time or moving objects.To study the computational behaviour of many-dimensional modal logics is the main aim of this book. On the one hand, it is concerned with providing a solid mathematical foundation for this discipline, while on the other hand, it shows that many seemingly different applied many-dimensional systems (e.g., multi-agent systems, description logics with epistemic, temporal and dynamic operators, spatio-temporal logics, etc.) fit in perfectly with this theoretical framework, and so their computational behaviour can be analyzed using the developed machinery.We start with concrete examples of applied one- and many-dimensional modal logics such as temporal, epistemic, dynamic, description, spatial logics, and various combinations of these. Then we develop a mathematical theory for handling a spectrum of 'abstract' combinations of modal logics - fusions and products of modal logics, fragments of first-order modal and temporal logics - focusing on three major problems: decidability, axiomatizability, and computational complexity. Besides the standard methods of modal logic, the technical toolkit includes the method of quasimodels, mosaics, tilings, reductions to monadic second-order logic, algebraic logic techniques. Finally, we apply the developed machinery and obtained results to three case studies from the field of knowledge representation and reasoning: temporal epistemic logics for reasoning about multi-agent systems, modalized description logics for dynamic ontologies, and spatio-temporal logics.The genre of the book can be defined as a research monograph. It brings the reader to the front line of current research in the field by showing both recent achievements and directions of future investigations (in particular, multiple open problems). On the other hand, well-known results from modal and first-order logic are formulated without proofs and supplied with references to accessible sources.The intended audience of this book is logicians as well as those researchers who use logic in computer science and artificial intelligence. More specific application areas are, e.g., knowledge representation and reasoning, in particular, terminological, temporal and spatial reasoning, or reasoning about agents. And we also believe that researchers from certain other disciplines, say, temporal and spatial databases or geographical information systems, will benefit from this book as well.Key Features:• Integrated approach to modern modal and temporal logics and their applications in artificial intelligence and computer science• Written by internationally leading researchers in the field of pure and applied logic• Combines mathematical theory of modal logic and applications in artificial intelligence and computer science• Numerous open problems for further research• Well illustrated with pictures and tables

Handbook of the Logic of Argument and Inference

  • 1st Edition
  • Volume 1
  • September 11, 2002
  • R.H. Johnson + 3 more
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 3 2 9 1 - 2
The Handbook of the Logic of Argument and Inference is an authoritative reference work in a single volume, designed for the attention of senior undergraduates, graduate students and researchers in all the leading research areas concerned with the logic of practical argument and inference. After an introductory chapter, the role of standard logics is surveyed in two chapters. These chapters can serve as a mini-course for interested readers, in deductive and inductive logic, or as a refresher. Then follow two chapters of criticism; one the internal critique and the other the empirical critique. The first deals with objections to standard logics (as theories of argument and inference) arising from the research programme in philosophical logic. The second canvasses criticisms arising from work in cognitive and experimental psychology. The next five chapters deal with developments in dialogue logic, interrogative logic, informal logic, probability logic and artificial intelligence. The last chapter surveys formal approaches to practical reasoning and anticipates possible future developments. Taken as a whole the Handbook is a single-volume indication of the present state of the logic of argument and inference at its conceptual and theoretical best. Future editions will periodically incorporate significant new developments.

Admissibility of Logical Inference Rules

  • 1st Edition
  • Volume 136
  • March 14, 1997
  • V.V. Rybakov
  • English
  • eBook
    9 7 8 - 0 - 0 8 - 0 5 2 5 9 9 - 0
The aim of this book is to present the fundamental theoretical results concerning inference rules in deductive formal systems. Primary attention is focused on:• admissible or permissible inference rules• the derivability of the admissible inference rules• the structural completeness of logics• the bases for admissible and valid inference rules.There is particular emphasis on propositional non-standard logics (primary, superintuitionistic and modal logics) but general logical consequence relations and classical first-order theories are also considered.The book is basically self-contained and special attention has been made to present the material in a convenient manner for the reader. Proofs of results, many of which are not readily available elsewhere, are also included.The book is written at a level appropriate for first-year graduate students in mathematics or computer science. Although some knowledge of elementary logic and universal algebra are necessary, the first chapter includes all the results from universal algebra and logic that the reader needs. For graduate students in mathematics and computer science the book is an excellent textbook.

Principles of Knowledge Representation and Reasoning

  • 1st Edition
  • June 8, 1994
  • Jon Doyle + 2 more
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 1 4 5 2 - 8
Principles of Knowledge Representation and Reasoning contains the proceedings of the Fourth International Conference on Principles of Knowledge Representation and Reasoning (KR '94) held in Bonn, Germany, on May 24-27, 1994. The conference provided a forum for reviewing the theory and principles underlying knowledge representation and reasoning. Topics covered range from reasoning about mental states and spatial reasoning with propositional logics to default logic as a query language. Comprised of 60 chapters, this book begins with a description of a formal language for representing and reasoning about time and action before turning to proof in context and how it can replace the most common uses of reflection principles. The reader is then introduced to reasoning with minimal models; belief ascription and mental-level modeling; and a unified framework for class-based representation formalisms. A general approach to specificity in default reasoning is also described, together with an ontology for engineering mathematics and the use of abduction to generate tests. The book concludes by considering the use of natural language for knowledge representation and reasoning. This monograph will be of interest to both students and practitioners in the fields of artificial intelligence and computer science.

Theoretical Aspects of Reasoning About Knowledge

  • 1st Edition
  • April 25, 1994
  • Ronald Fagin
  • English
  • eBook
    9 7 8 - 1 - 4 8 3 2 - 1 4 5 3 - 5
Theoretical Aspects of Reasoning About Knowledge contains the proceedings of the Fifth Conference on Theoretical Aspects of Reasoning About Knowledge (TARK 1994) held in Pacific Grove, California, on March 13-16, 1994. The conference provided a forum for discussing the theoretical aspects of reasoning about knowledge and tackled topics ranging from the logic of iterated belief revision and backwards forward induction to information acquisition from multi-agent resources, infinitely epistemic logic, and coherent belief revision in games. Comprised of 23 chapters, this book begins with a review of situation calculus and a solution to the frame problem, along with the use of a regression method for reasoning about the effect of actions. A novel programming language for high-level robotic control is described, along with a knowledge-based framework for belief change. Subsequent chapters deal with consistent belief reasoning in the presence of inconsistency; an epistemic logic of situations; an axiomatic approach to the logical omniscience problem; and an epistemic proof system for parallel processes. Inductive learning, knowledge asymmetries, and convention are also examined. This monograph will be of interest to both students and practitioners in the fields of artificial intelligence and computer science.