Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference

Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference by Ben Goertzel, Nil Geisweiller, Lucio Coelho, Predrag Janičić, Cassio Pennachin.

The general problem addressed in this book is a large and important one: how to usefully deal with huge storehouses of complex information about real-world situations. Every one of the major modes of interacting with such storehouses – querying, data mining, data analysis – is addressed by current t...

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Bibliographic Details
Main Authors: Goertzel, Ben (Author), Geisweiller, Nil (Author), Coelho, Lucio (Author), Janičić, Predrag (Author), Pennachin, Cassio (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Paris : Atlantis Press : Imprint: Atlantis Press, 2011.
Edition:1st ed. 2011.
Series:Atlantis Thinking Machines, 2
Springer eBook Collection.
Subjects:
Computer science.
Management information systems.
Artificial intelligence.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Introduction
  • Knowledge Representation Using Formal Logic
  • Quantifying and Managing Uncertainty
  • Representing Temporal Knowledge
  • Temporal Reasoning
  • Representing and Reasoning On Spatial Knowledge
  • Representing and Reasoning on Contextual Knowledge
  • Causal Reasoning
  • Extracting Logical Knowledge from Raw Data
  • Scalable Spatiotemporal Logical Knowledge Storage
  • Mining Patterns from Large Spatiotemporal Logical Knowledge Stores
  • Probabilistic Logic Networks
  • Temporal and Contextual Reasoning in PLN
  • Inferring the Causes of Observed Changes.-Adaptive Inference Control.

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