000			03198nam a22004935i 4500
001			978-0-387-09426-7
003			DE-He213
005			20140220083709.0
007			cr nn 008mamaa
008			110331s2011 xxu| s |||| 0|eng d
020			_a9780387094267 _9978-0-387-09426-7
024	7		_a10.1007/978-0-387-09426-7 _2doi
050		4	_aQ334-342
050		4	_aTJ210.2-211.495
072		7	_aUYQ _2bicssc
072		7	_aTJFM1 _2bicssc
072		7	_aCOM004000 _2bisacsh
082	0	4	_a006.3 _223
100	1		_aSanchez, Ernesto. _eauthor.
245	1	0	_aEvolutionary Optimization: the µGP toolkit _h[electronic resource] / _cby Ernesto Sanchez, Massimiliano Schillaci, Giovanni Squillero.
264		1	_aBoston, MA : _bSpringer US, _c2011.
300			_aXIII, 178 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aEvolutionary computation -- Why yet another one evolutionary optimizer? -- The μGP architecture -- Advanced features -- Performing an evolutionary run -- Command line syntax -- Syntax of the settings file -- Syntax of the population parameters file -- Syntax of the external constraints file -- Writing a compliant evaluator -- Implementation details -- Examples and applications -- Argument and option synopsis -- External constraints synopsis -- Index -- References.
520			_aThis book describes an award-winning evolutionary algorithm that outperformed experts and conventional heuristics in solving several industrial problems. It presents a discussion of the theoretical and practical aspects that enabled μGP (MicroGP) to autonomously find the optimal solution of hard problems, handling highly structured data, such as full-fledged assembly programs, with functions and interrupt handlers. For a practitioner, μGP is simply a versatile optimizer to tackle most problems with limited setup effort. The book is valuable for all who require heuristic problem-solving methodologies, such as engineers dealing with verification and test of electronic circuits; or researchers working in robotics and mobile communication. Examples are provided to guide the reader through the process, from problem definition to gathering results. For an evolutionary computation researcher, μGP may be regarded as a platform where new operators and strategies can be easily tested. MicroGP (the toolkit) is an active project hosted by Sourceforge: http://ugp3.sourceforge.net/
650		0	_aComputer science.
650		0	_aArtificial intelligence.
650		0	_aComputer aided design.
650	1	4	_aComputer Science.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aComputer Applications.
650	2	4	_aComputer-Aided Engineering (CAD, CAE) and Design.
700	1		_aSchillaci, Massimiliano. _eauthor.
700	1		_aSquillero, Giovanni. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387094250
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-09426-7
912			_aZDB-2-SCS
999			_c105012 _d105012