Quantified Representation of Uncertainty and Imprecision

Quantified Representation of Uncertainty and Imprecision PDF Author: Dov M. Gabbay
Publisher: Springer Science & Business Media
ISBN: 9780792351009
Category : Philosophy
Languages : en
Pages : 496

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Book Description
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.

Quantified Representation of Uncertainty and Imprecision

Quantified Representation of Uncertainty and Imprecision PDF Author: Dov M. Gabbay
Publisher: Springer Science & Business Media
ISBN: 9780792351009
Category : Philosophy
Languages : en
Pages : 496

Get Book Here

Book Description
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.

Reasoning about Uncertainty, second edition

Reasoning about Uncertainty, second edition PDF Author: Joseph Y. Halpern
Publisher: MIT Press
ISBN: 026234050X
Category : Computers
Languages : en
Pages : 505

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Book Description
Formal ways of representing uncertainty and various logics for reasoning about it; updated with new material on weighted probability measures, complexity-theoretic considerations, and other topics. In order to deal with uncertainty intelligently, we need to be able to represent it and reason about it. In this book, Joseph Halpern examines formal ways of representing uncertainty and considers various logics for reasoning about it. While the ideas presented are formalized in terms of definitions and theorems, the emphasis is on the philosophy of representing and reasoning about uncertainty. Halpern surveys possible formal systems for representing uncertainty, including probability measures, possibility measures, and plausibility measures; considers the updating of beliefs based on changing information and the relation to Bayes' theorem; and discusses qualitative, quantitative, and plausibilistic Bayesian networks. This second edition has been updated to reflect Halpern's recent research. New material includes a consideration of weighted probability measures and how they can be used in decision making; analyses of the Doomsday argument and the Sleeping Beauty problem; modeling games with imperfect recall using the runs-and-systems approach; a discussion of complexity-theoretic considerations; the application of first-order conditional logic to security. Reasoning about Uncertainty is accessible and relevant to researchers and students in many fields, including computer science, artificial intelligence, economics (particularly game theory), mathematics, philosophy, and statistics.

Symbolic and Quantitative Approaches to Reasoning and Uncertainty

Symbolic and Quantitative Approaches to Reasoning and Uncertainty PDF Author: Anthony Hunter
Publisher: Springer
ISBN: 3540487476
Category : Computers
Languages : en
Pages : 407

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Book Description
This book constitutes the refereed proceedings of the 1999 European Conference on Symbolic and Quantitative Approaches to Reasoning under Uncertainty, ECSQARU'99, held in London, UK, in July 1999. The 35 revised full papers presented were carefully reviewed and selected for inclusion in the book by the program committee. The volume covers theoretical as well as application-oriented aspects of various formalisms for reasoning under uncertainty. Among the issues addressed are default reasoning, nonmonotonic reasoning, fuzzy logic, Bayesian theory, probabilistic reasoning, inductive learning, rough knowledge discovery, Dempster-Shafer theory, qualitative decision making, belief functions, and evidence theory.

Conditionals, Information, and Inference

Conditionals, Information, and Inference PDF Author: Gabriele Kern-Isberner
Publisher: Springer Science & Business Media
ISBN: 3540253327
Category : Computers
Languages : en
Pages : 230

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Book Description
This book constitutes the thoroughly refereed postproceedings of the International Workshop on Conditionals, Information, and Inference, WCII 2002, held in Hagen, Germany in May 2002. The 9 revised full papers presented together with 3 invited papers by leading researchers in the area were carefully selected during iterated rounds of reviewing and improvement. The papers address all current issues of research on conditionals, ranging from foundational, theoretical, and methodological aspects to applications in various contexts of knowledge representation.

Probability and Social Science

Probability and Social Science PDF Author: Daniel Courgeau
Publisher: Springer Science & Business Media
ISBN: 9400728786
Category : Social Science
Languages : en
Pages : 333

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Book Description
This work examines in depth the methodological relationships that probability and statistics have maintained with the social sciences from their emergence. It covers both the history of thought and current methods. First it examines in detail the history of the different paradigms and axioms for probability, from their emergence in the seventeenth century up to the most recent developments of the three major concepts: objective, subjective and logicist probability. It shows the statistical inference they permit, different applications to social sciences and the main problems they encounter. On the other side, from social sciences—particularly population sciences—to probability, it shows the different uses they made of probabilistic concepts during their history, from the seventeenth century, according to their paradigms: cross-sectional, longitudinal, hierarchical, contextual and multilevel approaches. While the ties may have seemed loose at times, they have more often been very close: some advances in probability were driven by the search for answers to questions raised by the social sciences; conversely, the latter have made progress thanks to advances in probability. This dual approach sheds new light on the historical development of the social sciences and probability, and on the enduring relevance of their links. It permits also to solve a number of methodological problems encountered all along their history.

Reasoning about Uncertainty

Reasoning about Uncertainty PDF Author: Joseph Y. Halpern
Publisher: MIT Press
ISBN: 0262263076
Category : Computers
Languages : en
Pages : 498

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Book Description
Uncertainty is a fundamental and unavoidable feature of daily life; in order to deal with uncertaintly intelligently, we need to be able to represent it and reason about it. In this book, Joseph Halpern examines formal ways of representing uncertainty and considers various logics for reasoning about it. While the ideas presented are formalized in terms of definitions and theorems, the emphasis is on the philosophy of representing and reasoning about uncertainty; the material is accessible and relevant to researchers and students in many fields, including computer science, artificial intelligence, economics (particularly game theory), mathematics, philosophy, and statistics. Halpern begins by surveying possible formal systems for representing uncertainty, including probability measures, possibility measures, and plausibility measures. He considers the updating of beliefs based on changing information and the relation to Bayes' theorem; this leads to a discussion of qualitative, quantitative, and plausibilistic Bayesian networks. He considers not only the uncertainty of a single agent but also uncertainty in a multi-agent framework. Halpern then considers the formal logical systems for reasoning about uncertainty. He discusses knowledge and belief; default reasoning and the semantics of default; reasoning about counterfactuals, and combining probability and counterfactuals; belief revision; first-order modal logic; and statistics and beliefs. He includes a series of exercises at the end of each chapter.

Knowledge Science, Engineering and Management

Knowledge Science, Engineering and Management PDF Author: Franz Lehner
Publisher: Springer
ISBN: 3319476505
Category : Computers
Languages : en
Pages : 639

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Book Description
This book constitutes the refereed proceedings of the 9th International Conference on Knowledge Science, Engineering and Management, KSEM 2016, held in Passau, Germany, in October 2016. The 49 revised full papers presented together with 2 keynotes were carefully selected and reviewed from 116 submissions. The papers are organized in topical sections on Clustering and Classification; Text Mining and Lexical Analysis; Content and Document Analysis; Enterprise Knowledge; Formal Semantics and Fuzzy Logic; Knowledge Engineering; Knowledge Enrichment and Visualization; Knowledge Management; Knowledge Retrieval; Knowledge Systems and Security; Neural Networks and Artificial Intelligence; Ontologies; and Recommendation Algorithms and Systems.

Hybrid Intelligent Systems

Hybrid Intelligent Systems PDF Author: Ajith Abraham
Publisher: Springer Nature
ISBN: 3030493369
Category : Technology & Engineering
Languages : en
Pages : 470

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Book Description
This book highlights the recent research on hybrid intelligent systems and their various practical applications. It presents 34 selected papers from the 18th International Conference on Hybrid Intelligent Systems (HIS 2019) and 9 papers from the 15th International Conference on Information Assurance and Security (IAS 2019), which was held at VIT Bhopal University, India, from December 10 to 12, 2019. A premier conference in the field of artificial intelligence, HIS - IAS 2019 brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from 20 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.

Intelligent Data Engineering and Automated Learning – IDEAL 2019

Intelligent Data Engineering and Automated Learning – IDEAL 2019 PDF Author: Hujun Yin
Publisher: Springer Nature
ISBN: 3030336077
Category : Computers
Languages : en
Pages : 575

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Book Description
This two-volume set of LNCS 11871 and 11872 constitutes the thoroughly refereed conference proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2019, held in Manchester, UK, in November 2019. The 94 full papers presented were carefully reviewed and selected from 149 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2019 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models (including neural networks, evolutionary computation and swarm intelligence), agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI.

Intelligent Systems Design and Applications

Intelligent Systems Design and Applications PDF Author: Ajith Abraham
Publisher: Springer Nature
ISBN: 303096308X
Category : Technology & Engineering
Languages : en
Pages : 1461

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Book Description
This book highlights recent research on intelligent systems and nature-inspired computing. It presents 132 selected papers from the 21st International Conference on Intelligent Systems Design and Applications (ISDA 2021), which was held online. The ISDA is a premier conference in the field of computational intelligence, and the latest installment brought together researchers, engineers and practitioners whose work involves intelligent systems and their applications in industry. Including contributions by authors from 34 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.