Decentralized Reasoning in Ambient Intelligence: SpringerBriefs in Computer Science
Autor José Viterbo, Markus Endleren Limba Engleză Paperback – 25 mai 2012
Decentralized Reasoning in Ambient Intelligence proposes a decentralized reasoning approach for performing rule-based reasoning about context data targeting AmI systems. For this purpose, the authors define a context model assuming context data distributed over two sides: the user side, represented by the users and their mobile devices, and the ambient side, represented by the fixed computational infrastructure and ambient services. They formalize the cooperative reasoning operation — in which two entities cooperate to perform decentralized rule-based reasoning — and define a complete process to perform this operation.
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Specificații
ISBN-13: 9781447141679
ISBN-10: 1447141679
Pagini: 99
Ilustrații: IX, 96 p. 25 illus.
Dimensiuni: 155 x 235 x 15 mm
Greutate: 0.18 kg
Ediția:2012
Editura: SPRINGER LONDON
Colecția Springer
Seria SpringerBriefs in Computer Science
Locul publicării:London, United Kingdom
ISBN-10: 1447141679
Pagini: 99
Ilustrații: IX, 96 p. 25 illus.
Dimensiuni: 155 x 235 x 15 mm
Greutate: 0.18 kg
Ediția:2012
Editura: SPRINGER LONDON
Colecția Springer
Seria SpringerBriefs in Computer Science
Locul publicării:London, United Kingdom
Public țintă
ResearchCuprins
Introduction.- Fundamental Concepts.- Related Work.- Cooperative Reasoning.- Our Approach for Cooperative Reasoning.- Case Study.- Implementation.- Evaluation.- Conclusion.
Textul de pe ultima copertă
In Ambient Intelligence (AmI) systems, reasoning is fundamental for triggering actions or adaptations according to specific situations that may be meaningful and relevant to some applications. However, such reasoning operations may need to evaluate context data collected from distributed sources and stored in different devices, as usually not all context data is readily available to the reasoners within the system.
Decentralized Reasoning in Ambient Intelligence proposes a decentralized reasoning approach for performing rule-based reasoning about context data targeting AmI systems. For this purpose, the authors define a context model assuming context data distributed over two sides: the user side, represented by the users and their mobile devices, and the ambient side, represented by the fixed computational infrastructure and ambient services. They formalize the cooperative reasoning operation — in which two entities cooperate to perform decentralized rule-based reasoning — and define a complete process to perform this operation.
Decentralized Reasoning in Ambient Intelligence proposes a decentralized reasoning approach for performing rule-based reasoning about context data targeting AmI systems. For this purpose, the authors define a context model assuming context data distributed over two sides: the user side, represented by the users and their mobile devices, and the ambient side, represented by the fixed computational infrastructure and ambient services. They formalize the cooperative reasoning operation — in which two entities cooperate to perform decentralized rule-based reasoning — and define a complete process to perform this operation.
Caracteristici
Presents a detailed description of how to implement a decentralized reasoning mechanism for intelligent ambients Includes supplementary material: sn.pub/extras