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Uncertainty Theory

A Branch of Mathematics for Modeling Human Uncertainty

  • Book
  • © 2010

Overview

Authors:
  1. Baoding Liu

    1. Department of Mathematical Sciences, Tsinghua University, Beijing, China

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  • Recent research in Agents and multi-agent systems in distributed systems
  • Presents new applications of multi-agent systems to digital economy and e-commerce
  • Written by a leading expert in the field

Part of the book series: Studies in Computational Intelligence (SCI, volume 300)

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Table of contents (11 chapters)

  1. Front Matter

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  2. Uncertainty Theory

    • Baoding Liu
    Pages 1-79

  3. Uncertain Programming

    • Baoding Liu
    Pages 81-113

  4. Uncertain Risk Analysis

    • Baoding Liu
    Pages 115-123

  5. Uncertain Reliability Analysis

    • Baoding Liu
    Pages 125-130

  6. Uncertain Process

    • Baoding Liu
    Pages 131-138

  7. Uncertain Calculus

    • Baoding Liu
    Pages 139-145

  8. Uncertain Differential Equation

    • Baoding Liu
    Pages 147-161

  9. Uncertain Logic

    • Baoding Liu
    Pages 163-175

  10. Uncertain Entailment

    • Baoding Liu
    Pages 177-186

  11. Uncertain Set Theory

    • Baoding Liu
    Pages 187-213

  12. Uncertain Inference

    • Baoding Liu
    Pages 215-223

  13. Back Matter

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Keywords

About this book

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.

Authors and Affiliations

  • Department of Mathematical Sciences, Tsinghua University, Beijing, China

    Baoding Liu

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