Principles of quantum artificial intelligence / Andreas Wichert.

Format:

Book

Author/Creator:

Wichert, Andrzej.

Contributor:

ebrary, Inc.

Language:

English

Subjects (All):

Artificial intelligence.

Quantum computers.

Physical Description:

1 online resource ( xiv, 262 pages) : illustrations

monochrome

Place of Publication:

Singapore ; Hackensack, NJ : World Scientific, [2014]

System Details:

text file

Summary:

In this book, we introduce quantum computation and its application to AI. We highlight problem solving and knowledge representation framework. Based on information theory, we cover two main principles of quantum computation - Quantum Fourier transform and Grover search. Then, we indicate how these two principles can be applied to problem solving and finally present a general model of a quantum computer that is based on production systems. Key Features: Introduces a new subarea of Al û Quantum Artificial Intelligence, Orients itself on computer science by merging AI and Quantum Computation principles Book jacket.

Contents:

1. Introduction. 1.1. Artificial intelligence. 1.2. Motivation and goals. 1.3. Guide to the reader. 1.4. Content

2. Computation. 2.1. Entscheidungsproblem. 2.2. Complexity theory. 2.3. Church-Turing thesis. 2.4. Computers

3. Problem solving. 3.1. Knowledge representation. 3.2. Production system. 3.3. Sub-symbolic models of problem-solving

4. Information. 4.1. Information and thermodynamics. 4.2. Hierarchical structures. 4.3. Information and measurement. 4.4. Information and memory. 4.5. Sparse code for sub-symbols. 4.6. Deduction systems and associative memory

5. Reversible algorithms. 5.1. Reversible computation. 5.2. Reversible circuits

6. Probability. 6.1. Kolmogorovs probabilities. 6.2. Mixed distribution. 6.3. Markov chains

7. Introduction to quantum physics. 7.1. Unitary evolution. 7.2. Quantum mechanics. 7.3. Hilbert space. 7.4. Quantum time evolution. 7.5. Compound systems. 7.6. Von Neumann entropy. 7.7. Measurement. 7.8. Randomness

8. Computation with qubits. 8.1. Computation with one qubit. 8.2. Computation with m qubit. 8.3. Matrix representation of serial and parallel operations. 8.4. Entanglement. 8.5. Quantum Boolean circuits. 8.6. Deutsch algorithm. 8.7. Deutsch Jozsa algorithm. 8.8. Amplitude distribution. 8.9. Geometric operations

9. Periodicity. 9.1. Fourier transform. 9.2. Discrete Fourier transform. 9.3. Quantum Fourier transform. 9.4. FFT. 9.5. QFT decomposition. 9.6. QFT properties. 9.7. The QFT period algorithm. 9.8. Factorization. 9.9. Kitaev's phase estimation algorithm. 9.10. Unitary transforms

10. Search. 10.1. Search and quantum oracle. 10.2. Lower bound [symbol] for [symbol]-based search. 10.3. Grover's amplification. 10.4. Circuit representation. 10.5. Speeding up the traveling salesman problem. 10.6. The generate-and-test method

11. Quantum problem-solving. 11.1. Symbols and quantum reality. 11.2. Uninformed tree search. 11.3. Heuristic search. 11.4. Quantum tree search. 11.5. Quantum production system. 11.6. Tarrataca's quantum production system. 11.7. A general model of a quantum computer

12. Quantum cognition. 12.1. Quantum probability. 12.2. Decision making. 12.3. Unpacking effects. 12.4. Conclusion

13. Related approaches. 13.1. Quantum walk. 13.2. Adiabatic computation. 13.3. Quantum neural computation. 13.4. Epilogue.

Notes:

Includes bibliographical references (pages 247-257) and index.

Electronic reproduction. Palo Alto, Calif. Available via World Wide Web.

Description based on online resource; title from digital title page (viewed on Dec. 19, 2013).

ISBN:

9789814566759

9814566756

Access Restriction:

Restricted for use by site license. Single-user access only.