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Quantum AI is one of today’s most rapidly growing fields, which has attracted enormous attention from not only research scientists but also the public and press. However, hitherto there is no such a book that introduces quantum AI to readers in a relatively comprehensive and up-to-date way. In particular, a comprehensive text book at the graduate level or higher with exercise problems for quantum AI is highly desirable, given that more and more universities/colleges begin to open quantum AI-related courses and more and more students and researchers become interested in this interdisciplinary field. Quantum Artificial Intelligence aims to fill this gap.
Chapter 1. Introduction
Chapter 2. Basics of artificial intelligence
Chapter 3. Basics of quantum computation and quantum information
Chapter 4. Quantum algorithms for machine learning
Chapter 5. Quantum artificial neural networks
Chapter 6. Quantum classifiers
Chapter 7. Quantum reinforcement learning
Chapter 8. Quantum autoencoder
Chapter 9. Quantum problem-solving and quantum cognition
Chapter 10. Quantum generative learning
Chapter 11. Complexity theory on quantum learning
Chapter 12. Machine learning phases of matter
Chapter 13. Solving quantum many-body problems with artificial neural networks
Chapter 14. Quantum adversarial machine learning
Chapter 15. Experimental advances
Chapter 16. Conclusion and outlook