Artificial Intelligence for the Internet of Everything

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
		2.3.3. Example: Logistic Regression
		2.3.4. 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
	3.2. The Challenges of Autonomous Intelligence on the Battlefield
	3.3. 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
		4.2.4. Behavior Workflow and Computational Considerations
	4.3. 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
Chapter 5: Policy Issues Regarding Implementations of Cyber Attack: Resilience Solutions for Cyber Physical Systems
	5.1. 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
Chapter 6: Trust and Human-Machine Teaming: A Qualitative Study
	6.1. Background
		6.1.1. Human-Machine Trust
		6.1.2. Human-Machine Teaming
		6.1.3. Perceived Agency
		6.1.4. Perceived Benevolence
		6.1.5. Perceived Task Interdependence
		6.1.6. Relationship-Building
		6.1.7. Communication Richness
		6.1.8. Synchrony
	6.2. Method
		6.2.1. Participants
		6.2.2. Study Description and Items
		6.2.3. Coding Method
		6.2.4. Trust
		6.2.5. Human-Machine Teaming
	6.3. Results
	6.4. Discussion
	6.5. Conclusion
	References
	Further Reading
Chapter 7: The Web of Smart Entities-Aspects of a Theory of the Next Generation of the Internet of Things
	7.1. Introduction
	7.2. Smart Things
	7.3. A Vision of the Next Generation of the IoT
		7.3.1. Interlude
	7.4. The Use of Artificial Intelligence in the Web of Smart Entities
	7.5. Towards a Theory of the Web of Smart Entities
		7.5.1. Real-Time Data
		7.5.2. Real-Time Models
		7.5.3. Automation
		7.5.4. Web of Smart Entities
		7.5.5. Changing Roles of Stakeholders
	7.6. Interacting With Automation
		7.6.1. Fully Autonomous
		7.6.2. Semiautonomous
		7.6.3. Manual
		7.6.4. Extent of Automation
	7.7. Depth of WSE
	7.8. Conclusions
	Acknowledgments
	References
Chapter 8: Raising Them Right: AI and the Internet of Big Things
	8.1. Introduction
	8.2. ``Things Are About to Get Weird´´
	8.3. Raise Them Right
	8.4. Learning to Live With It
Chapter 9: The Value of Information and the Internet of Thingsa
	9.1. Introduction
	9.2. The Internet of Things and Artificial Intelligence
	9.3. Reworking Howard's Initial Example
	9.4. Value Discussion
		9.4.1. Generalization
	9.5. Clairvoyance About C
	9.6. Clairvoyance About L
	9.7. Clairvoyance About C and L
	9.8. Discussion
	9.9. Conclusion
	Acknowledgments
	References
Chapter 10: Would IOET Make Economics More Neoclassical or More Behavioral? Richard Thalers Prediction, a Revisit
	10.1. Motivation and Introduction
	10.2. Walrasian Auctioneer and Unmanned Markets
	10.3. Homo Economicus vs. Homo Sapiens
		10.3.1. Cyborgs
		10.3.2. Trend Reversal
		10.3.3. Trend Sustaining
	10.4. Concluding Remarks
	Acknowledgments
	References
Chapter 11: Accessing Validity of Argumentation of Agents of the Internet of Everything
	11.1. Introduction
	11.2. Representing Argumentative Discourse
	11.3. Detecting Invalid Argumentation Patterns
	11.4. Recognizing Communicative Discourse Trees for Argumentation
	11.5. Assessing Validity of Extracted Argument Patterns Via Dialectical Analysis
	11.6. Intense Arguments Dataset
	11.7. Evaluation of Detection and Validation of Arguments
	11.8. Conclusions
	References
	Further Reading
Chapter 12: Distributed Autonomous Energy Organizations: Next-Generation Blockchain Applications for Energy Infrastructure
	12.1. Introduction to Distributed Autonomous Energy Organizations
		12.1.1. DAEO Enablers: AI and Blockchain
	12.2. Distributed Energy Supply Chain
	12.3. AI-Blockchain to Secure Your Energy Supply Chain
	12.4. Potential Blockchain Business and Implementation Challenges
	12.5. Roadmap for When to Use Blockchain in the Energy Sector
	12.6. The Evolution of Public Key Infrastructure Encryption
	12.7. Why Blockchain, Why DAEO
	12.8. Overview of the AI-Enabled Blockchain
	12.9. Blockchain and AI Security Opportunity
	12.10. Conclusion and Future Research
	References
	Further Reading
Chapter 13: Compositional Models for Complex Systems
	13.1. Introduction
	13.2. Characteristics of Complex Systems
		13.2.1. Heterogeneity of Components
		13.2.2. Open Interaction
		13.2.3. Multiplicity of Perspectives
		13.2.4. Joint Cognition
	13.3. System Design Is a Recursive Process
	13.4. Inductive Datatypes and Algebraic Structures
	13.5. Coalgebra and Infinite Datatypes
	13.6. Operads as Compositional Architectures
	13.7. Architectures for Learning
	13.8. Conclusion
	Disclaimer
	References
Chapter 14: Meta-Agents: Using Multi-Agent Networks to Manage Dynamic Changes in the Internet of Things
	14.1. Introduction
	14.2. Managing Complexity
	14.3. Sentry AGEnts
	14.4. An Illustrative Example
	14.5. Reasoning
	14.6. Challenges and Conclusion
	Acknowledgments
	References
Index
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