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Titlebook: Decentralized Reasoning in Ambient Intelligence; José Viterbo,Markus Endler Book 2012 The Author(s) 2012 Ambient Intelligence.Distributed

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書目名稱Decentralized Reasoning in Ambient Intelligence
編輯José Viterbo,Markus Endler
視頻videohttp://file.papertrans.cn/265/264151/264151.mp4
概述Presents a detailed description of how to implement a decentralized reasoning mechanism for intelligent ambients.Includes supplementary material:
叢書名稱SpringerBriefs in Computer Science
圖書封面Titlebook: Decentralized Reasoning in Ambient Intelligence;  José Viterbo,Markus Endler Book 2012 The Author(s) 2012 Ambient Intelligence.Distributed
描述.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..
出版日期Book 2012
關(guān)鍵詞Ambient Intelligence; Distributed Inference; Rule-based Reasoning; Ubiquitous Computing
版次1
doihttps://doi.org/10.1007/978-1-4471-4168-6
isbn_softcover978-1-4471-4167-9
isbn_ebook978-1-4471-4168-6Series ISSN 2191-5768 Series E-ISSN 2191-5776
issn_series 2191-5768
copyrightThe Author(s) 2012
The information of publication is updating

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Case Study,two different examples, a client query (synchronous interaction) and a client subscription (asynchronous interaction). For both cases we assume that the context data distribution corresponds to what was shown in Fig.?..
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José Viterbo,Markus EndlerPresents a detailed description of how to implement a decentralized reasoning mechanism for intelligent ambients.Includes supplementary material:
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