Probabilistic Logic Networks A Comprehensive Framework for Uncertain Inference /

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...

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Bibliographic Details
Call Number:Libro Electrónico
Main Authors: Goertzel, Ben (Author), Iklé, Matthew (Author), Goertzel, Izabela Freire (Author), Heljakka, Ari (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:Inglés
Published: New York, NY : Springer US : Imprint: Springer, 2009.
Edition:1st ed. 2009.
Subjects:
Artificial intelligence.
Computer science-Mathematics.
Artificial Intelligence.
Mathematical Applications in Computer Science.
Online Access:Texto Completo
Table of Contents:
  • Knowledge Representation
  • Experiential Semantics
  • Indefinite Truth Values
  • First-Order Extensional Inference: Rules and Strength Formulas
  • First-Order Extensional Inference with Indefinite Truth Values
  • First-Order Extensional Inference with Distributional Truth Values
  • Error Magnification in Inference Formulas
  • Large-Scale Inference Strategies
  • Higher-Order Extensional Inference
  • Handling Crisp and Fuzzy Quantifiers with Indefinite Truth Values
  • Intensional Inference
  • Aspects of Inference Control
  • Temporal and Causal Inference.

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