This book covers the fundamental principles, new theories and
methodologies, and potential applications of hybrid intelligent
networks. Chapters focus on hybrid neural networks and networked
multi-agent networks, including their communication, control and
optimization synthesis. This text also provides a succinct but useful
guideline for designing neural network-based hybrid artificial
intelligence for brain-inspired computation systems and applications in
the Internet of Things.
Artificial Intelligence has developed into a deep research field
targeting robots with more brain-inspired perception, learning,
decision-making abilities, etc. This text devoted to a tutorial on
hybrid intelligent networks that have been identified in nature and
engineering, especially in the brain, modeled by hybrid dynamical
systems and complex networks, and have shown potential application to
brain-inspired intelligence. Included in this text are impulsive neural
networks, neurodynamics, multiagent networks, hybrid dynamics analysis,
collective dynamics, as well as hybrid communication, control and
optimization methods.
Graduate students who are interested in artificial intelligence and
hybrid intelligence, as well as professors and graduate students who are
interested in neural networks and multiagent networks will find this
textbook a valuable resource. AI engineers and consultants who are
working in wireless communications and networking will want to buy this
book. Also, professional and academic institutions in universities and
Mobile vehicle companies and engineers and managers who concern humans
in the loop of IoT will also be interested in this book.
