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Machines like us : toward AI with common sense / Ronald J. Brachman and Hector J. Levesque.

By: Contributor(s): Material type: TextLanguage: English Publisher: Cambridge, Massachusetts : The MIT Press, 2022Description: xii, 306 pages : illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780262046794 (hardcover)
  • 0262046792 (hardcover)
Subject(s): DDC classification:
  • 006.3
LOC classification:
  • Q 335 B796m 2022
Contents:
The Road to Common Sense -- Common Sense in Humans -- Expertise in AI Systems -- Knowledge and Its Representation -- A Commonsense Understanding of the World -- Commonsense Knowledge -- Representation and Reasoning, Part I -- Representation and Reasoning, Part II -- Common Sense in Action -- Steps toward Implementation -- Building Trust -- Epilogue -- Appendix -- Bonus Chapter: The Logic of Common Sense
Summary: "The authors of Machines Like Us explore what it would take to endow computers with the kind of common sense that humans depend on every day--critically needed for AI systems to be successful in the world and to become trustworthy"-- Provided by publisher.
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Holdings
Item type Current library Home library Collection Shelving location Call number Copy number Status Barcode
Libro Biblioteca Juan Bosch Biblioteca Juan Bosch Humanidades Humanidades (4to. Piso) Q 335 B796m 2022 (Browse shelf(Opens below)) 1 Available 00000192816

Includes bibliographical references (pages 249-295) and index.

The Road to Common Sense -- Common Sense in Humans -- Expertise in AI Systems -- Knowledge and Its Representation -- A Commonsense Understanding of the World -- Commonsense Knowledge -- Representation and Reasoning, Part I -- Representation and Reasoning, Part II -- Common Sense in Action -- Steps toward Implementation -- Building Trust -- Epilogue -- Appendix -- Bonus Chapter: The Logic of Common Sense

"The authors of Machines Like Us explore what it would take to endow computers with the kind of common sense that humans depend on every day--critically needed for AI systems to be successful in the world and to become trustworthy"-- Provided by publisher.

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