Artificial Intelligence for the Internet of Everything

ISBN-13: 9780128176368 / Angielski / Miękka / 2019 / 303 str.

William Lawless; Ranjeev Mittu; Donald Sofge

Spis treści

1. Introduction 2. Uncertainty Quantification in Internet of Battlefield Things 3. Intelligent Autonomous Things on the Battlefield 4. Active Inference in Multi-agent Systems: Context-driven Collaboration and Decentralized Purpose-driven Team Adaptation 5. Policy Issues Regarding Implementations of Cyber Attack. Resilience Solutions for Cyber Physical Systems 6. Trust and Human-Machine Teaming: A Qualitative Study 7. The Web of Smart Entities - Aspects of a Theory of the Next Generation of the Internet of Things 8. Raising Them Right: AI and the Internet of Big Things 9. Valuable Information and the Internet of Things 10. Would IOET Make Economics More Neoclassical or More Behavioral? Richard Thaler's Prediction, A Revisit 11. Accessing Validity of Argumentation of Agents of the Internet of Everything 12. Distributed Autonomous Energy Organizations: Next Generation Blockchain Applications for Energy Infrastructure 13. Compositional Models for Complex Systems 14. Meta-agents: Using Multi-Agent Networks to Manage Dynamic Changes in the Internet of Things (IoT)

O autorze

William Lawless is professor of mathematics and psychology at Paine College, GA. For his PhD topic on group dynamics, he theorized about the causes of tragic mistakes made by large organizations with world-class scientists and engineers. After his PhD in 1992, DOE invited him to join its citizens advisory board (CAB) at DOE's Savannah River Site (SRS), Aiken, SC. As a founding member, he coauthored numerous recommendations on environmental remediation from radioactive wastes (e.g., the regulated closure in 1997 of the first two high-level radioactive waste tanks in the USA). He is a member of INCOSE, IEEE, AAAI and AAAS. His research today is on autonomous human-machine teams (A-HMT). He is the lead editor of seven published books on artificial intelligence. He was lead organizer of a special issue on "human-machine teams and explainable AI” by AI Magazine (2019). He has authored over 85 articles and book chapters, and over 175 peer-reviewed proceedings. He was the lead organizer of twelve AAAI symposia at Stanford (2020). Since 2018, he has also been serving on the Office of Naval Research's Advisory Boards for the Science of Artificial Intelligence and Command Decision Making. Ranjeev Mittu is the branch head for the Information Management and Decision Architectures Branch within the Information Technology Division at the U.S. Naval Research Laboratory (NRL). He leads a multidisciplinary group of scientists and engineers that conduct research and advanced development in visual analytics, human performance assessment, decision support systems, and enterprise systems. Mr. Mittu's research expertise is in multi-agent systems, human-systems integration, artificial intelligence (AI), machine learning, data mining and pattern recognition; and he has authored and/or coedited nine books on the topic of AI in collaboration with national and international scientific communities spanning academia and defense. Mr. Mittu received a Master of Science Degree in Electrical Engineering in 1995 from The Johns Hopkins University in Baltimore, MD. Don Sofge is a computer scientist and roboticist at the Naval Research Laboratory (NRL) with 33 years of experience in artificial intelligence, machine learning, and control systems R&D. He leads the Distributed Autonomous Systems Group in the Navy Center for Applied Research in Artificial Intelligence (NCARAI), where he develops nature-inspired computing paradigms to challenging problems in sensing, artificial intelligence, and control of autonomous robotic systems. He has more than 180 refereed publications including 10 books in robotics, artificial intelligence, machine learning, planning, sensing, control, and related disciplines. Dr. Moskowitz has been a mathematician at the Naval Research Laboratory (NRL) for 29 years; presently, he is in the Information Management and Decision Architectures Branch within NRL's Information Technology Division. Prior to his work at NRL, he was a mathematics professor. His PhD was in Differential Topology from Stony Brook University, Stony Brook, New York. His research areas are information theory and information hiding. His major contributions have been to the area of covert channel analysis. He has over 120 publications and three patents. In particular he is the co-inventor of the NRL Network Pump ®. Dr. Russell is currently the Battlefield Information Processing Branch Chief at the Army Research Laboratory. Dr. Russell received a B.Sc. in Computer Science and M.S. and Ph.D. degrees in Information Systems from the University of Maryland. His primary research interests are in the area of decision support systems, machine learning, systems architectures, and intelligent systems. His published research articles appear in Expert Systems with Applications, Decision Support Systems Journal, the Encyclopedia of Decision Making and Decision Support Technologies, and Frontiers in Bioscience, amongst others.