Principles of quantum artificial intelligence : quantum problem solving and machine learning / Andreas Wichert, Instituto Superior Tecnico - Universidade de Lisboa, Portugal.

By: Wichert, Andreas [author.]Material type: TextTextLanguage: English Publisher: New Jersey : World Scientific, 2020Copyright date: ©2020Edition: Second EditionDescription: 478 pages : illustrations, charts ; 24 cmContent type: text | still image Media type: unmediated Carrier type: volumeISBN: 9789811224300 (hardback)Subject(s): Artificial intelligence | Computers -- Computer Literacy | Computer science | Data processing | Verilog (Computer hardware description language) | Information technology | Quantum PhysicsLOC classification: Q335 .W53 2020
Contents:
1. Introduction.
2. Computation.
3. Problem Solving.
4. Information.
5. Reversible Algorithms.
6. Probability.
7. Introduction to Quantum Physics.
8. Computation with Qubits.
9. Periodicity.
10. Search.
11. Quantum Problem-Solving.
12. Grover's Algorithm and the Input Problem.
13. Statistical Machine Learning.
14. Linear-Algebra Based Quantum Machine Learning.
15. Stochastic Methods.
16. Adiabatic Quantum Computation and Quantum Annealing.
17. Quantum Cognition.
18. Quantum like-Evolution.
19. Quantum Computation and the Multiverse.
20. Conclusion.
Subject: This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods and quantum computation. It indicates how to apply quantum computation to problem solving, machine learning and quantum-like models to decision making — the core disciplines of artificial intelligence. Most of the chapters were rewritten and extensive new materials were updated. New topics include quantum machine learning, quantum-like Bayesian networks and mind in Everett many-worlds. https://www.worldscientific.com/worldscibooks/10.1142/11938
Item type Current library Shelving location Call number Status Date due Barcode
Books MEF Üniversitesi Kütüphanesi
Genel Koleksiyon Q 335 .W53 2020 (Browse shelf (Opens below)) Checked out 02.06.2025 0020282

"for Andre"

Includes bibliographical references (pages 455-471) and index (pages 473-478).

1. Introduction.

2. Computation.

3. Problem Solving.

4. Information.

5. Reversible Algorithms.

6. Probability.

7. Introduction to Quantum Physics.

8. Computation with Qubits.

9. Periodicity.

10. Search.

11. Quantum Problem-Solving.

12. Grover's Algorithm and the Input Problem.

13. Statistical Machine Learning.

14. Linear-Algebra Based Quantum Machine Learning.

15. Stochastic Methods.

16. Adiabatic Quantum Computation and Quantum Annealing.

17. Quantum Cognition.

18. Quantum like-Evolution.

19. Quantum Computation and the Multiverse.

20. Conclusion.

This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods and quantum computation. It indicates how to apply quantum computation to problem solving, machine learning and quantum-like models to decision making — the core disciplines of artificial intelligence.

Most of the chapters were rewritten and extensive new materials were updated. New topics include quantum machine learning, quantum-like Bayesian networks and mind in Everett many-worlds.

https://www.worldscientific.com/worldscibooks/10.1142/11938