000			04319nam a22004575i 4500
003			DE-He213
005			20191011020353.0
007			cr nn 008mamaa
008			100301s2007 xxu| s |||| 0|eng d
020	6	4	_a9780387367910 _9978-0-387-36791-0
024	8	7	_a10.1007/978-0-387-36791-0 _2doi
100	8	1	_aSpector, Lee. _eeditor. _919719
245	9	7	_aAutomatic Quantum Computer Programming _h[electronic resource] : _bA Genetic Programming Approach / _cedited by Lee Spector.
001			000045672
300	6	4	_aXII, 154 p. _bonline resource.
490	8	1	_aGenetic Programming, _x1566-7863 ; _v7
505	8	0	_aThe Power of Quantum Computing -- Quantum Computer Simulation -- Quantum Computer Programming -- Genetic and Evolutionary Computation -- Genetic Programming -- Evolution of Complex Programs -- Evolution of Quantum Programs -- Evolved Quantum Programs -- Conclusions and Prospects.
520	6	4	_aComputer science will be radically transformed if ongoing efforts to build large-scale quantum computers eventually succeed and if the properties of these computers meet optimistic expectations. Nevertheless, computer scientists still lack a thorough understanding of the power of quantum computing, and it is not always clear how best to utilize the power that it is understood. This dilemma exists because quantum algorithms are difficult to grasp and even more difficult to write. Despite large-scale international efforts, only a few important quantum algorithms are documented, leaving many essential questions about the potential of quantum algorithms unanswered. These unsolved problems are ideal challenges for the application of automatic programming technologies. Genetic programming techniques, in particular, have already produced several new quantum algorithms and it is reasonable to expect further discoveries in the future. Theses methods will help researchers to discover how additional practical problems can be solved using quantum computers, and they will also help to guide theoretical work on both the power and limits of quantum computing. Automatic Quantum Computer Programming provides an introduction to quantum computing for non-physicists, as well as an introduction to genetic programming for non-computer-scientists. The book explores several ways in which genetic programming can support automatic quantum computer programming and presents detailed descriptions of specific techniques, along with several examples of their human-competitive performance on specific problems. Source code for the authors QGAME quantum computer simulator is included as an appendix, and pointers to additional online resources furnish the reader with an array of tools for automatic quantum computer programming. "I thoroughly enjoyed this book. It not only introduces quantum computing, but also genetic programming and the authors original genetic programming system PushGP which is used to evolve the quantum algorithms discussed in later chapters. The book is comprehensive, with wonderfully clear illustrations and comes with a Lisp-based quantum simulator program. Truly recommended for readers interested in gaining knowledge about exciting frontiers of computer science." Wolfgang Banzhaf Memorial University of Newfoundland
650	8	0	_aComputer science. _919720
650	8	0	_aSoftware engineering. _99213
650	8	0	_aArtificial intelligence. _98970
650	8	0	_aQuantum computing. _912355
650			_aComputer Science. _919721
650			_aSoftware Engineering/Programming and Operating Systems. _99913
650			_aProgramming Techniques. _910862
650			_aArtificial Intelligence (incl. Robotics). _98973
650			_aQuantum Computing, Information and Physics. _912358
710	8	2	_aSpringerLink (Online service) _919722
773	8	0	_tSpringer eBooks
776			_iPrinted edition: _z9780387364964
830	8	0	_aGenetic Programming, _x1566-7863 ; _v7 _919723
856			_uhttp://dx.doi.org/10.1007/978-0-387-36791-0 _zde clik aquí para ver el libro electrónico
264	8	1	_aBoston, MA : _bSpringer US, _c2007.
336	6	4	_atext _btxt _2rdacontent
337	6	4	_acomputer _bc _2rdamedia
338	6	4	_aonline resource _bcr _2rdacarrier
347	6	4	_atext file _bPDF _2rda
516	6	4	_aZDB-2-SCS
999			_c45401 _d45401
942			_c05