Artificial intelligence for the Internet of everything

Considering the foundations, metrics and applications of Internet of Everything (IoE) systems, this book covers whether devices and IoE systems should speak only to each other, to humans or to both. --

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Bibliographic Details
Other Authors: Lawless, William, (Editor), Mittu, Ranjeev, (Editor), Sofge, Donald, (Editor), Moskowitz, Ira S., 1956- (Editor), Russell, Stephen, (Editor)
Format: eBook
Language: English
Published: London : Academic Press, an imprint of Elsevier, [2019]
Subjects:
Artificial intelligence.
Internet.
elektronické knihy
electronic books
ISBN: 9780128176375
0128176377
9780128176368
0128176369
Physical Description: 1 online resource

Cover

Table of contents

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035 |a (OCoLC)1088407329  |z (OCoLC)1088544122  |z (OCoLC)1229512944 
245 0 0 |a Artificial intelligence for the Internet of everything /  |c edited by William Lawless, Ranjeev Mittu, Donald Sofge, Ira S. Moskowitz, Stephen Russell. 
264 1 |a London :  |b Academic Press, an imprint of Elsevier,  |c [2019] 
264 4 |c ©2019 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
505 0 |a Front Cover; Artificial Intelligence For The Internet of Everything; Copyright; Contents; Contributors; Chapter 1: Introduction; 1.1. Introduction: IoE: IoT, IoBT, and IoIT-Background and Overview; 1.2. Introductions to the Technical Chapters; References; Chapter 2: Uncertainty Quantification in Internet of Battlefield Things; 2.1. Introduction; 2.2. Background and Motivating IoBT Scenario; 2.2.1. Detecting Vehicle-Borne IEDs in Urban Environments; 2.3. Optimization in Machine Learning; 2.3.1. Optimization Problem; 2.3.2. Stochastic Gradient Descent Algorithm 
505 8 |a 2.3.3. Example: Logistic Regression2.3.4. SGD Variants; 2.3.4.1. Mini-Batch SGD; 2.3.4.2. SGD With Momentum; 2.3.5. Nesterov's Accelerated Gradient Descent; 2.3.6. Generalized Linear Models; 2.3.7. Learning Feature Representations for Inference; 2.4. Uncertainty Quantification in Machine Learning; 2.4.1. Gaussian Process Regression; 2.4.2. Neural Network; 2.4.3. Uncertainty Quantification in Deep Neural Network; 2.5. Adversarial Learning in DNN; 2.6. Summary and Conclusion; References; Chapter 3: Intelligent Autonomous Things on the Battlefield; 3.1. Introduction 
505 8 |a 3.2. The Challenges of Autonomous Intelligence on the Battlefield3.3. AI Will Fight the Cyber Adversary; 3.4. AI Will Perceive the Complex World; 3.5. AI Enables Embodied Agents; 3.6. Coordination Requires AI; 3.7. Humans in the Ocean of Things; 3.8. Summary; References; Further Reading; Chapter 4: Active Inference in Multiagent Systems: Context-Driven Collaboration and Decentralized Purpose-Driven Team Ada ... ; 4.1. Introduction; 4.2. Energy-Based Adaptive Agent Behaviors; 4.2.1. Free Energy Principle; 4.2.2. Adaptive Behavior and Context; 4.2.3. Formal Definitions 
505 8 |a 4.2.4. Behavior Workflow and Computational Considerations4.3. Application of Energy Formalism to Multiagent Teams; 4.3.1. Motivation; 4.3.2. Problem Definition; 4.3.3. Distributed Collaborative Search Via Free Energy Minimization; 4.3.4. Adapting Team Structure; 4.4. Validation Experiments; 4.4.1. Experiment Setup; 4.4.2. Discrete Decision Making Versus Free Energy; 4.4.3. Impact of Agent Network Structure; 4.4.4. Impact of Decision Decomposition; 4.5. Conclusions; References; Further Reading 
505 8 |a Chapter 5: Policy Issues Regarding Implementations of Cyber Attack: Resilience Solutions for Cyber Physical Systems5.1. Introduction: Context; 5.2. The Need to Address Cybersecurity for Physical Systems; 5.2.1. Historic Patterns for Addressing Cybersecurity; 5.2.2. Mission-Based Cybersecurity; 5.2.3. Education of Engineers and Policy-Makers; 5.3. Cybersecurity Role and Certification of the Operators of Physical Systems; 5.4. Data Curation; 5.5. Market Incentives; 5.6. Conclusions and Recommendations; Acknowledgments; References; Further Reading 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a Considering the foundations, metrics and applications of Internet of Everything (IoE) systems, this book covers whether devices and IoE systems should speak only to each other, to humans or to both. --  |c Edited summary from book. 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Artificial intelligence. 
650 0 |a Internet. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Lawless, William,  |e editor. 
700 1 |a Mittu, Ranjeev,  |e editor. 
700 1 |a Sofge, Donald,  |e editor. 
700 1 |a Moskowitz, Ira S.,  |d 1956-  |e editor.  |1 https://id.oclc.org/worldcat/entity/E39PCjtWQchGx4FDrrBmC8G8md 
700 1 |a Russell, Stephen,  |e editor. 
776 0 8 |i Print version:  |t Artificial intelligence for the Internet of everything.  |d London : Academic Press, an imprint of Elsevier, [2019]  |z 0128176369  |z 9780128176368  |w (OCoLC)1052876634 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpAIIE0001/artificial-intelligence-for?kpromoter=marc  |y Full text 

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