The research on Quantum Networked Artificial Intelligence is at the intersection of Quantum Information Science (QIS), Artificial Intelligence, Soft Computing, Computational Intelligence, Machine Learning, Deep Learning, Optimization, Etc. It Touches On Many Important Parts Of Near-Term Quantum Computing And Noisy Intermediate-Scale Quantum (NISQ) Devices. The research on quantum artificial intelligence is grounded in theories, modelling, and significant studies on hybrid classical-quantum algorithms using classical simulations, IBM Q services, PennyLane, Google Cirq, D-Wave quantum annealer etc. So far, the research on quantum artificial intelligence has given us the building blocks to achieve quantum advantage to solve problems in combinatorial optimization, soft computing, deep learning, and machine learning much faster than traditional classical computing. Solving these problems is important for making quantum computing useful for noise-resistant large-scale applications. This makes it much easier to see the big picture and helps with cutting-edge research across the quantum stack, making it an important part of any QIS effort. Researchers — almost daily — are making advances in the engineering and scientific challenges to create practical quantum networks powered with artificial intelligence.
Quantum Networks and its Applications in Artificial Intelligence have reached a point where their broad implementation requires the participation of several disciplines. The objective of this QNAAI is to investigate the potential uses of artificial intelligence and related technologies in quantum networks and to educate the computational intelligence community about current advances in quantum information technology. Numerous quantum information and processing systems have been created and proven in labs, fields, and commercial settings during the last few decades. Software engineers employ best practices to create reliable and scalable software solutions, ensuring the delivery of high-quality applications. The union of Quantum Networks and Artificial Intelligence marks a pivotal moment in the trajectory of technological advancement. This encompasses data security, optimization, finance, high-precision sensors, simulations, and computer applications. Quantum technologies have received considerable support for research and development from corporations and governments. However, considerable work is required to bring quantum technology-based gadgets and systems to consumers' homes. In addition, many challenges provide chances to contribute knowledge, technology, and engineering from outside the field of artificial intelligence. The purpose of this research topic is to bring together individuals from academia and industry, from the classical and quantum artificial intelligence communities, to discuss the theory, technology, and applications of quantum technologies, and to exchange ideas on how to efficiently advance the engineering and development of this fascinating field. The book will open doors for Quantum Computing Professionals to come up with real world applications of Quantum Networks as an Effective tool to portfolio optimization and route planning. This Book will be a Key Reference for Students, Practitioners, Professionals, Scientists and Engineer – Researchers to combat the shortcomings of the Quantum Electronics - Machine Computing Models