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

Ben Goertzel

ISBN 10: 9462390533 / ISBN 13: 9789462390539

Published by Atlantis Press (Zeger Karssen), 2014

About this Item

Paperback. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9789462390539

Bibliographic Details

• Title: Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference (Paperback)
• Publisher: Atlantis Press (Zeger Karssen)
• Publication Date: 2014
• Language: English
• ISBN 10: 9462390533
• ISBN 13: 9789462390539
• Binding: Paperback
• Condition: new

About this title

Synopsis

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.