Mathematical Models for Handling Partial Knowledge in Artificial Intelligence
Mathematical Models for Handling Partial Knowledge in Artificial Intelligence

Author: Giulianella Coletti

Publisher: Springer Science & Business Media

Published: 2013-06-29

Total Pages: 311

ISBN-13: 1489914242

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Knowledge acquisition is one of the most important aspects influencing the quality of methods used in artificial intelligence and the reliability of expert systems. The various issues dealt with in this volume concern many different approaches to the handling of partial knowledge and to the ensuing methods for reasoning and decision making under uncertainty, as applied to problems in artificial intelligence. The volume is composed of the invited and contributed papers presented at the Workshop on Mathematical Models for Handling Partial Knowledge in Artificial Intelligence, held at the Ettore Majorana Center for Scientific Culture of Erice (Sicily, Italy) on June 19-25, 1994, in the framework of the International School of Mathematics "G.Stampacchia". It includes also a transcription of the roundtable held during the workshop to promote discussions on fundamental issues, since in the choice of invited speakers we have tried to maintain a balance between the various schools of knowl edge and uncertainty modeling. Choquet expected utility models are discussed in the paper by Alain Chateauneuf: they allow the separation of perception of uncertainty or risk from the valuation of outcomes, and can be of help in decision mak ing. Petr Hajek shows that reasoning in fuzzy logic may be put on a strict logical (formal) basis, so contributing to our understanding of what fuzzy logic is and what one is doing when applying fuzzy reasoning.

PRICAI 2008: Trends in Artificial Intelligence
PRICAI 2008: Trends in Artificial Intelligence

Author: Tu-Bao Ho

Publisher: Springer

Published: 2008-12-04

Total Pages: 1154

ISBN-13: 3540891978

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The Pacific Rim International Conference on Artificial Intelligence (PRICAI) is one of the preeminent international conferences on artificial intelligence (AI). PRICAI 2008 (http://www.jaist.ac.jp/PRICAI-08/) was the tenth in this series of biennial int- national conferences highlighting the most significant contributions to the field of AI. The conference was held during December 15–19, 2008, in the beautiful city Hanoi, the capital of Vietnam. As in previous years this year’s technical program saw very high standards in both the submission and paper review process, resulting in an exciting program that reflects the great variety and depth of modern AI research. This year’s contributions covered all traditional areas of AI, including AI foundations, knowledge representation, knowledge acquisition and ontologies, evolutionary computation, etc., as well as va- ous exciting and innovative applications of AI to many different areas. There was particular emphasis in the areas of machine learning and data mining, intelligent agents, language and speech processing, information retrieval and extraction.

Fuzzy Logic in Artificial Intelligence
Fuzzy Logic in Artificial Intelligence

Author: Anca L. Ralescu

Publisher: Springer Science & Business Media

Published: 1999-07-28

Total Pages: 264

ISBN-13: 9783540663744

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This volume constitutes the thoroughly refereed post-workshop proceedings of an international workshop on fuzzy logic in Artificial Intelligence held in Negoya, Japan during IJCAI '97. The 17 revised full papers presented have gone through two rounds of reviewing and revision. Three papers by leading authorities in the area are devoted to the general relevance of fuzzy logic and fuzzy sets to AI. The remaining papers address various relevant issues ranging from theory to application in areas like knowledge representation, induction, logic programming, robotics, pattern recognition, etc.

System Modelling and Optimization
System Modelling and Optimization

Author: J. Dolezal

Publisher: Springer

Published: 2013-06-05

Total Pages: 635

ISBN-13: 0387348972

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Proceedings volume contains carefully selected papers presented during the 17th IFIP Conference on System Modelling and Optimization. Optimization theory and practice, optimal control, system modelling, stochastic optimization, and technical and non-technical applications of the existing theory are among areas mostly addressed in the included papers. Main directions are treated in addition to several survey papers based on invited presentations of leading specialists in the respective fields. Publication provides state-of-the-art in the area of system theory and optimization and points out several new areas (e.g fuzzy set, neural nets), where classical optimization topics intersects with computer science methodology.

Applications of Uncertainty Formalisms
Applications of Uncertainty Formalisms

Author: Anthony Hunter

Publisher: Springer

Published: 2003-06-29

Total Pages: 481

ISBN-13: 354049426X

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An introductory review of uncertainty formalisms by the volume editors begins the volume. The first main part of the book introduces some of the general problems dealt with in research. The second part is devoted to case studies; each presentation in this category has a well-delineated application problem and an analyzed solution based on an uncertainty formalism. The final part reports on developments of uncertainty formalisms and supporting technology, such as automated reasoning systems, that are vital to making these formalisms applicable. The book ends with a useful subject index. There is considerable synergy between the papers presented. The representative collection of case studies and associated techniques make the volume a particularly coherent and valuable resource. It will be indispensable reading for researchers and professionals interested in the application of uncertainty formalisms as well as for newcomers to the topic.

Probabilistic Analysis of Belief Functions
Probabilistic Analysis of Belief Functions

Author: Ivan Kramosil

Publisher: Springer Science & Business Media

Published: 2001-12-31

Total Pages: 236

ISBN-13: 9780306467028

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Inspired by the eternal beauty and truth of the laws governing the run of stars on heavens over his head, and spurred by the idea to catch, perhaps for the smallest fraction of the shortest instant, the Eternity itself, man created such masterpieces of human intellect like the Platon's world of ideas manifesting eternal truths, like the Euclidean geometry, or like the Newtonian celestial me chanics. However, turning his look to the sub-lunar world of our everyday efforts, troubles, sorrows and, from time to time but very, very seldom, also our successes, he saw nothing else than a world full of uncertainty and tem porariness. One remedy or rather consolation was that of the deep and sage resignation offered by Socrates: I know, that I know nothing. But, happy or unhappy enough, the temptation to see and to touch at least a very small por tion of eternal truth also under these circumstances and behind phenomena charged by uncertainty was too strong. Probability theory in its most sim ple elementary setting entered the scene. It happened in the same, 17th and 18th centuries, when celestial mechanics with its classical Platonist paradigma achieved its greatest triumphs. The origins of probability theory were inspired by games of chance like roulettes, lotteries, dices, urn schemata, etc. and probability values were simply defined by the ratio of successful or winning results relative to the total number of possible outcomes.

Belief Change
Belief Change

Author: Dov M. Gabbay

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 452

ISBN-13: 9401150540

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Belief change is an emerging field of artificial intelligence and information science dedicated to the dynamics of information and the present book provides a state-of-the-art picture of its formal foundations. It deals with the addition, deletion and combination of pieces of information and, more generally, with the revision, updating and fusion of knowledge bases. The book offers an extensive coverage of, and seeks to reconcile, two traditions in the kinematics of belief that often ignore each other - the symbolic and the numerical (often probabilistic) approaches. Moreover, the work encompasses both revision and fusion problems, even though these two are also commonly investigated by different communities. Finally, the book presents the numerical view of belief change, beyond the probabilistic framework, covering such approaches as possibility theory, belief functions and convex gambles. The work thus presents a unified view of belief change operators, drawing from a widely scattered literature embracing philosophical logic, artificial intelligence, uncertainty modelling and database systems. The material is a clearly organised guide to the literature on the dynamics of epistemic states, knowledge bases and uncertain information, suitable for scholars and graduate students familiar with applied logic, knowledge representation and uncertain reasoning.

XML Topic Maps
XML Topic Maps

Author: Jack Park

Publisher: Addison-Wesley Professional

Published: 2003

Total Pages: 642

ISBN-13: 9780201749601

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XML Topic Maps is designed to be a "living document" for managing information across the Web's interconnected resources. The book begins with a broad introduction and a tutorial on topic maps and XTM technology. The focus then shifts to strategies for creating and deploying the technology. Throughout, the latest theoretical perspectives are offered, alongside discussions of the challenges developers will face as the Web continues to evolve. Looking forward, the book's concluding chapters provide a road map to the future of topic map technology and the Semantic Web in general.

Advances in Intelligent Computing - IPMU '94
Advances in Intelligent Computing - IPMU '94

Author: Bernadette Bouchon-Meunier

Publisher: Springer Science & Business Media

Published: 1995-06-26

Total Pages: 648

ISBN-13: 9783540601166

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

Data Mining, Rough Sets and Granular Computing
Data Mining, Rough Sets and Granular Computing

Author: Tsau Young Lin

Publisher: Physica

Published: 2013-11-11

Total Pages: 538

ISBN-13: 3790817910

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During the past few years, data mining has grown rapidly in visibility and importance within information processing and decision analysis. This is par ticularly true in the realm of e-commerce, where data mining is moving from a "nice-to-have" to a "must-have" status. In a different though related context, a new computing methodology called granular computing is emerging as a powerful tool for the conception, analysis and design of information/intelligent systems. In essence, data mining deals with summarization of information which is resident in large data sets, while granular computing plays a key role in the summarization process by draw ing together points (objects) which are related through similarity, proximity or functionality. In this perspective, granular computing has a position of centrality in data mining. Another methodology which has high relevance to data mining and plays a central role in this volume is that of rough set theory. Basically, rough set theory may be viewed as a branch of granular computing. However, its applications to data mining have predated that of granular computing.