Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference (Atlantis Thinking Machines, #2)

by Ben Goertzel, Nil Geisweiller, Lucio Coelho, Predrag Janicic, and Cassio Pennachin

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

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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 technologies only in very limited and unsatisfactory ways. The impact of a solution to this problem would be huge and pervasive, as the domains of human pursuit to which such storehouses are acutely relevant is numerous and rapidly growing. Finally, we give a more detailed treatment of one potential solution with this class, based on our prior work with the Probabilistic Logic Networks (PLN) formalism. We show how PLN can be used to carry out realworld reasoning, by means of a number of practical examples of reasoning regarding human activities inreal-world situations.
  • ISBN13 9789491216107
  • Publish Date 7 December 2011 (first published 1 January 2011)
  • Publish Status Active
  • Publish Country NL
  • Imprint Atlantis Press (Zeger Karssen)
  • Edition 2011
  • Format Hardcover
  • Pages 269
  • Language English