000			03701cam a22002415i 4500
001			18016832
003			ISI Library, Kolkata
005			20141208123817.0
008			140123s2014 si a b 001 0 eng
020			_a9789814566742 (hbk.)
040			_aISI Library
082			_223 _bW633 _a004.1
100	1		_aWichert, Andreas.
245	1	0	_aPrinciples of quantum artificial intelligence / _cAndreas Wichert.
260			_aSingapore : _bWorld Scientific, _cc2014.
300			_axiv, 202 p. : _bill. ; _c24 cm.
504			_aIncludes bibliographical references (p. 247-257) and index.
505			_a1. 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. Bibliography-- Index.
520			_aIn 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.
650		0	_aQuantum computers.
650		0	_aArtificial intelligence.
942			_2ddc _cBK
999			_c416213 _d416213