Probabilistic Logic Networks

A Comprehensive Framework for Uncertain Inference

Authors: Goertzel, B., Iklé, M., Goertzel, I.F., Heljakka, A.

  • Provides a comprehensive framework for uncertain reasoning, integrating probability theory, predicate and term logic, and pattern theory
  • Considers a broad scope of reasoning types
  • Fuses rigorous mathematics with practical computation to describe methods designed for large-scale and, in many cases, real-time inference within commercial software systems
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About this book

This book describes Probabilistic Logic Networks (PLN), a novel conceptual, mathematical and computational approach to uncertain inference. Going beyond prior probabilistic approaches to uncertain inference, PLN encompasses such ideas as induction, abduction, analogy, fuzziness and speculation, and reasoning about time and causality. The book provides an overview of PLN in the context of other approaches to uncertain inference. Topics addressed in the text include:

    • the basic formalism of PLN knowledge representation
    • the conceptual interpretation of the terms used in PLN
    • an indefinite probability approach to quantifying uncertainty, providing a general method for calculating the "weight-of-evidence" underlying the conclusions of uncertain inference
    • specific PLN inference rules and the corresponding truth-value formulas used to determine the strength of the conclusion of an inference rule from the strengths of the premises
    • large-scale inference strategies
    • inference using variables
    • indefinite probabilities involving quantifiers
    • inheritance based on properties or patterns
    • the Novamente Cognition Engine, an application of PLN
    • temporal and causal logic in PLN

Researchers and graduate students in artificial intelligence, computer science, mathematics and cognitive sciences will find this novel perspective on uncertain inference a thought-provoking integration of ideas from a variety of other lines of inquiry.

Table of contents (14 chapters)

  • Error Magnification in Inference Formulas

    Goertzel, Ben (et al.)

    Pages 1-30

  • Experiential Semantics

    Goertzel, Ben (et al.)

    Pages 1-7

  • Introduction

    Goertzel, Ben (et al.)

    Pages 1-21

  • Large-Scale Inference Strategies

    Goertzel, Ben (et al.)

    Pages 1-22

  • Handling Crisp and Fuzzy Quantifiers with Indefinite Truth Values

    Goertzel, Ben (et al.)

    Pages 1-10

Buy this book

eBook n/a
  • ISBN 978-0-387-76872-4
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
Hardcover n/a
  • ISBN 978-0-387-76871-7
  • Free shipping for individuals worldwide
Softcover n/a
  • ISBN 978-1-4419-4578-5
  • Free shipping for individuals worldwide

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Bibliographic Information

Bibliographic Information
Book Title
Probabilistic Logic Networks
Book Subtitle
A Comprehensive Framework for Uncertain Inference
Authors
Copyright
2009
Publisher
Springer US
Copyright Holder
Springer-Verlag US
eBook ISBN
978-0-387-76872-4
DOI
10.1007/978-0-387-76872-4
Hardcover ISBN
978-0-387-76871-7
Softcover ISBN
978-1-4419-4578-5
Edition Number
1
Number of Pages
VIII, 336
Topics