My Account Log in

3 options

Principles of quantum artificial intelligence / Andreas Wichert, Instituto Superior Tecnico - Universidade de Lisboa, Portugal.

EBSCOhost Academic eBook Collection (North America) Available online

View online

EBSCOhost eBook Community College Collection Available online

View online

Ebook Central Academic Complete Available online

View online
Format:
Book
Author/Creator:
Wichert, Andrzej.
Series:
Gale eBooks
Language:
English
Subjects (All):
Quantum computers.
Artificial intelligence.
Physical Description:
1 online resource (xiv, 202 pages) : illustrations
Place of Publication:
New Jersey : World Scientific, [2014]
Language Note:
English
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.
Contents:
Preface; Contents; 1. Introduction; 1.1 Artificial Intelligence; 1.2 Motivation and Goals; 1.3 Guide to the Reader; 1.4 Content; 1.4.1 Classical computation; 1.4.2 Quantum computation; 2. Computation; 2.1 Entscheidungsproblem; 2.1.1 Cantor's diagonal argument; 2.1.2 Reductio ad absurdum; 2.2 Complexity Theory; 2.2.1 Decision problems; 2.2.2 P and NP; 2.3 Church-Turing Thesis; 2.3.1 Church-Turing-Deutsch principle; 2.4 Computers; 2.4.1 Analog computers; 2.4.2 Digital computers; 2.4.3 Von Neumann architecture; 3. Problem Solving; 3.1 Knowledge Representation; 3.1.1 Rules
3.1.2 Logic-based operators3.1.3 Frames; 3.1.4 Categorial representation; 3.1.5 Binary vector representation; 3.2 Production System; 3.2.1 Deduction systems; 3.2.2 Reaction systems; 3.2.3 Conflict resolution; 3.2.4 Human problem-solving; 3.2.5 Example; 3.3 Sub-Symbolic Models of Problem-Solving; 3.3.1 Proto logic; 3.3.2 Binding problem; 3.3.3 Icons; 3.3.4 Euclidian geometry of the world; 4. Information; 4.1 Information and Thermodynamics; 4.1.1 Dice model; 4.1.2 Entropy; 4.1.3 Maxwell paradox and information; 4.1.4 Information theory; 4.2 Hierarchical Structures; 4.2.1 Example of a taxonomy
4.3 Information and Measurement4.3.1 Information measure I; 4.3.2 Nature of information measure; 4.3.3 Measurement of angle; 4.3.4 Information and contour; 4.4 Information and Memory; 4.5 Sparse code for Sub-symbols; 4.5.1 Sparsification based on unary sub-vectors; 4.6 Deduction Systems and Associative Memory; 4.6.1 Taxonomic knowledge organization; 5. Reversible Algorithms; 5.1 Reversible Computation; 5.2 Reversible Circuits; 5.2.1 Boolean gates; 5.2.2 Reversible Boolean gates; 5.2.3 Toffoli gate; 5.2.4 Circuit; 6. Probability; 6.1 Kolmogorovs Probabilities; 6.1.1 Conditional probability
6.1.2 Bayes's rule6.1.3 Joint distribution; 6.1.3.1 Example; 6.1.4 Naıve Bayes and counting; 6.1.5 Counting and categorization; 6.1.6 Bayesian networks; 6.1.6.1 Example; 6.2 Mixed Distribution; 6.3 Markov Chains; 7. Introduction to Quantum Physics; 7.1 Unitary Evolution; 7.1.1 Schrodinger's cat paradox; 7.1.2 Interpretations of quantum mechanics; 7.2 Quantum Mechanics; 7.2.1 Stochastic Markov evolution and unitary evolution; 7.3 Hilbert Space; 7.3.1 Spectral representation*; 7.4 Quantum Time Evolution; 7.5 Compound Systems; 7.6 Von Neumann Entropy; 7.7 Measurement; 7.7.1 Observables
7.7.2 Measuring a compound system7.7.3 Heisenberg's uncertainty principle*; 7.8 Randomness; 7.8.1 Deterministic chaos; 7.8.2 Kolmogorov complexity; 7.8.3 Humans and random numbers; 7.8.4 Randomness in quantum physics; 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; 8.8.1 Cloning; 8.8.2 Teleportation; 8.9 Geometric Operations; 9. Periodicity; 9.1 Fourier Transform
9.2 Discrete Fourier Transform
Notes:
Description based upon print version of record.
Includes bibliographical references and index.
Description based on online resource; title from PDF title page (ebrary, viewed December 2, 2013).
ISBN:
9789814566759
9814566756
OCLC:
897557791

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account