Download handbook of temporal reasoning in artificial intelligence foundations of artificial intelligence in pdf or read handbook of temporal reasoning in artificial intelligence foundations of artificial intelligence in pdf online books in PDF, EPUB and Mobi Format. Click Download or Read Online button to get handbook of temporal reasoning in artificial intelligence foundations of artificial intelligence in pdf book now. This site is like a library, Use search box in the widget to get ebook that you want.

Handbook Of Temporal Reasoning In Artificial Intelligence

Author: Michael David Fisher
Publisher: Elsevier
ISBN: 9780080533360
Size: 18.73 MB
Format: PDF, ePub, Mobi
View: 6486
Download and Read
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 · 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

Handbook Of Knowledge Representation

Author: Frank van Harmelen
Publisher: Elsevier
ISBN: 9780080557021
Size: 53.92 MB
Format: PDF, Docs
View: 5255
Download and Read
Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems. This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering. This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI. * Make your computer smarter * Handle qualitative and uncertain information * Improve computational tractability to solve your problems easily

Handbook Of Constraint Programming

Author: Francesca Rossi
Publisher: Elsevier
ISBN: 9780080463803
Size: 52.22 MB
Format: PDF, Mobi
View: 1585
Download and Read
Constraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, computer science, databases, programming languages, and operations research. Constraint programming is currently applied with success to many domains, such as scheduling, planning, vehicle routing, configuration, networks, and bioinformatics. The aim of this handbook is to capture the full breadth and depth of the constraint programming field and to be encyclopedic in its scope and coverage. While there are several excellent books on constraint programming, such books necessarily focus on the main notions and techniques and cannot cover also extensions, applications, and languages. The handbook gives a reasonably complete coverage of all these lines of work, based on constraint programming, so that a reader can have a rather precise idea of the whole field and its potential. Of course each line of work is dealt with in a survey-like style, where some details may be neglected in favor of coverage. However, the extensive bibliography of each chapter will help the interested readers to find suitable sources for the missing details. Each chapter of the handbook is intended to be a self-contained survey of a topic, and is written by one or more authors who are leading researchers in the area. The intended audience of the handbook is researchers, graduate students, higher-year undergraduates and practitioners who wish to learn about the state-of-the-art in constraint programming. No prior knowledge about the field is necessary to be able to read the chapters and gather useful knowledge. Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas. The handbook is organized in two parts. The first part covers the basic foundations of constraint programming, including the history, the notion of constraint propagation, basic search methods, global constraints, tractability and computational complexity, and important issues in modeling a problem as a constraint problem. The second part covers constraint languages and solver, several useful extensions to the basic framework (such as interval constraints, structured domains, and distributed CSPs), and successful application areas for constraint programming. - Covers the whole field of constraint programming - Survey-style chapters - Five chapters on applications

Foundations Of Knowledge Representation And Reasoning

Author: Gerhard Lakemeyer
Publisher: Springer Science & Business Media
ISBN: 9783540581079
Size: 22.87 MB
Format: PDF, ePub
View: 3456
Download and Read
The papers collected in this book cover a wide range of topics in asymptotic statistics. In particular up-to-date-information is presented in detection of systematic changes, in series of observation, in robust regression analysis, in numerical empirical processes and in related areas of actuarial sciences and mathematical programming. The emphasis is on theoretical contributions with impact on statistical methods employed in the analysis of experiments and observations by biometricians, econometricians and engineers.

An Introduction To Constraint Based Temporal Reasoning

Author: Roman Barták
Publisher: Morgan & Claypool Publishers
ISBN: 1681731770
Size: 42.98 MB
Format: PDF, ePub
View: 4778
Download and Read
Solving challenging computational problems involving time has been a critical component in the development of artificial intelligence systems almost since the inception of the field. This book provides a concise introduction to the core computational elements of temporal reasoning for use in AI systems for planning and scheduling, as well as systems that extract temporal information from data. It presents a survey of temporal frameworks based on constraints, both qualitative and quantitative, as well as of major temporal consistency techniques. The book also introduces the reader to more recent extensions to the core model that allow AI systems to explicitly represent temporal preferences and temporal uncertainty. This book is intended for students and researchers interested in constraint-based temporal reasoning. It provides a self-contained guide to the different representations of time, as well as examples of recent applications of time in AI systems.

Spatial And Temporal Reasoning

Author: O. Stock
Publisher: Springer Science & Business Media
ISBN: 0585283222
Size: 58.43 MB
Format: PDF, Mobi
View: 6284
Download and Read
Qualitative reasoning about space and time - a reasoning at the human level - promises to become a fundamental aspect of future systems that will accompany us in daily activity. The aim of Spatial and Temporal Reasoning is to give a picture of current research in this area focusing on both representational and computational issues. The picture emphasizes some major lines of development in this multifaceted, constantly growing area. The material in the book also shows some common ground and a novel combination of spatial and temporal aspects of qualitative reasoning. Part I presents the overall scene. The chapter by Laure Vieu is on the state of the art in spatial representation and reasoning, and that by Alfonso Gerevini gives a similar survey on research in temporal reasoning. The specific contributions to these areas are then grouped in the two main parts. In Part II, Roberto Casati and Achille Varzi examine the ontological status of spatial entities; Anthony Cohn, Brandon Bennett, John Gooday, and Nicholas Gotts present a detailed theory of reasoning with qualitative relations about regions; Andrew Frank discusses the spatial needs of geographical information systems; and Annette Herskovits focuses on the linguistic expression of spatial relations. In Part III, James Allen and George Ferguson describe an interval temporal logic for the representation of actions and events; Drew McDermott presents an efficient way of predicting the outcome of plan execution; and Erik Sandewall introduces a semantics based on transitions for assessing theories of action and change. In Part IV, Antony Galton's chapter stands clearly between the two areas of space and time and outlines the main coordinates of an integrated approach.

Many Dimensional Modal Logics Theory And Applications

Author: A. Kurucz
Publisher: Elsevier
ISBN: 9780080535784
Size: 15.70 MB
Format: PDF
View: 4456
Download and Read
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

Web Reasoning And Rule Systems

Author: Roman Kontchakov
Publisher: Springer
ISBN: 3319111132
Size: 50.20 MB
Format: PDF, ePub, Mobi
View: 7114
Download and Read
This book constitutes the refereed proceedings of the 8th International Conference on Web Reasoning and Rule Systems, RR 2014, held in Athens, Greece in September 2014. The 9 full papers, 9 technical communications and 5 poster presentations presented together with 3 invited talks, 3 doctoral consortial papers were carefully reviewed and selected from 33 submissions. The conference covers a wide range of the following: semantic Web, rule and ontology languages, and related logics, reasoning, querying, searching and optimization, incompleteness, inconsistency and uncertainty, non-monotonic, common sense, and closed-world reasoning for the web, dynamic information, stream reasoning and complex event processing, decision making, planning, and intelligent agents, machine learning, knowledge extraction and information retrieval, data management, data integration and reasoning on the web of data, ontology-based data access, system descriptions, applications and experiences.

Enterprise Information Systems

Author: Joaquim Filipe
Publisher: Springer Science & Business Media
ISBN: 3642198015
Size: 79.19 MB
Format: PDF, ePub
View: 4272
Download and Read
This book contains substantially extended and revised versions of the best papers from the 12th International Conference on Enterprise Information Systems (ICEIS 2010), held in Funchal, Madeira, Portugal, June 8-12, 2010. Two invited papers are presented together with 39 contributions, which were carefully reviewed and selected from 62 full papers presented at the conference (out of 448 submissions). They reflect state-of-the-art research work that is often driven by real-world applications, thus successfully relating the academic with the industrial community. The topics covered are: databases and information systems integration, artificial intelligence and decision support systems, information systems analysis and specification, software agents and internet computing, and human-computer interaction.

Solving The Frame Problem

Author: Murray Shanahan
Publisher: MIT Press
ISBN: 9780262193849
Size: 70.98 MB
Format: PDF, ePub, Mobi
View: 5654
Download and Read
"Shanahan gives a clear exposition of the AI problem in general and logical AI in particular. He goes on to a clear exposition of the frame problem and many approaches to its solution. Much of this will become accepted as authoritative." -- John McCarthy, Professor of Computer Science, Stanford University "The frame problem is one of the central theoretical issues of artificial intelligence, and considerable progress in the study of this problem has been made over the last years. Shanahan's book provides a clear and comprehensive treatment of this work. It will be appreciated by everyone interested in the logical foundations of artificial intelligence." -- Vladimir Lifschitz, Gottesman Family Centennial Professor in Computer Sciences, University of Texas at Austin In 1969, John McCarthy and Pat Hayes uncovered a problem that has haunted the field of artificial intelligence ever since--the frame problem. The problem arises when logic is used to describe the effects of actions and events. Put simply, it is the problem of representing what remains unchanged as a result of an action or event. Many researchers in artificial intelligence believe that its solution is vital to the realization of the field's goals. "Solving the Frame Problem" presents the various approaches to the frame problem that have been proposed over the years. The author presents the material chronologically--as an unfolding story rather than as a body of theory to be learned by rote. There are lessons to be learned even from the dead ends researchers have pursued, for they deepen our understanding of the issues surrounding the frame problem. In the book'sconcluding chapters, the author offers his own work on event calculus, which he claims comes very close to a complete solution to the frame problem. "Artificial Intelligence series"