000			04072nam a22005415i 4500
001			978-0-387-75164-1
003			DE-He213
005			20180115171418.0
007			cr nn 008mamaa
008			110413s2009 xxu| s |||| 0|eng d
020			_a9780387751641 _9978-0-387-75164-1
024	7		_a10.1007/978-0-387-75164-1 _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		_aAndrew, Alex M. _eauthor.
245	1	2	_aA Missing Link in Cybernetics _h[electronic resource] : _bLogic and Continuity / _cby Alex M. Andrew.
264		1	_aNew York, NY : _bSpringer New York, _c2009.
300			_aXI, 139 p. 4 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aIFSR International Series on Systems Science and Engineering, _x1574-0463 ; _v26
505	0		_aCybernetics: Origins and Aims -- Where to Start? -- Continuous versus Discrete -- Adaptation, Self-Organisation, Learning -- Backpropagation -- Self-Reference -- Fractal Intelligence -- Conclusions.
520			_aThe relative failure of attempts to analyze and model intelligence can be attributed in part to the customary assumption that the processing of continuous variables and the manipulation of discrete concepts should be treated separately. In this book, the author considers concept-based thought as having evolved from processing of continuous variables. Although "fuzzy" theory acknowledges the need to combine conceptual and continuous processing, its assumption of the primacy of concept-based processing makes it evolutionarily implausible. The text begins by reviewing the origins and aims of cybernetics with particular reference to Warren McCulloch’s declared lifetime quest of "understanding man’s understanding". It is shown that continuous systems can undergo complex self-organization, but a need for classification of situations becomes apparent and can be seen as the evolutionary beginning of concept-based processing. Possibilities for complex self-organization are emphasized by discussion of a general principle that has been termed significance feedback, of which backpropagation of errors in neural nets is a special case. It is also noted that continuous measures come to be associated with processing that is essentially concept-based, as acknowledged in Marvin Minsky’s reference to heuristic connection between problems, and the associated basic learning heuristic of Minsky and Selfridge. This reappearance of continuity, along with observations on the multi-layer structure of intelligent systems, supports a potentially valuable view of intelligence as having a fractal nature. This is such that structures at a complex level, interpreted in terms of these emergent measures, reflect others at a simpler level. Implications for neuroscience and Artificial Intelligence are also examined. The book presents unconventional and challenging viewpoints that will be of interest to researchers in AI, psychology, cybernetics and systems science, and should help promote further research.
650		0	_aComputer science.
650		0	_aArtificial intelligence.
650		0	_aApplied mathematics.
650		0	_aEngineering mathematics.
650		0	_aSystem theory.
650		0	_aMathematical logic.
650	1	4	_aComputer Science.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aMathematical Logic and Foundations.
650	2	4	_aApplications of Mathematics.
650	2	4	_aSystems Theory, Control.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387751634
830		0	_aIFSR International Series on Systems Science and Engineering, _x1574-0463 ; _v26
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-75164-1
912			_aZDB-2-SMA
999			_c369674 _d369674