Probabilistic Logic Networks A Comprehensive Framework for Uncertain Inference /

• Main Authors: Goertzel, Ben (Author), Iklé, Matthew (Author), Goertzel, Izabela Freire (Author), Heljakka, Ari (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Boston, MA : Springer US, 2009.
• Subjects: Computer science.; Computer science > Mathematics.; Artificial intelligence.; Computer Science.; Artificial Intelligence (incl. Robotics).; Math Applications in Computer Science.

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...

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.