000			02900nam a22003975i 4500
001			978-0-387-87488-3
003			DE-He213
005			20251006084426.0
007			cr nn 008mamaa
008			110406s2009 xxu| s |||| 0|eng d
020			_a9780387874883
020			_a99780387874883
024	7		_a10.1007/978-0-387-87488-3 _2doi
100	1		_aGunderson, James P. _eauthor.
245	1	0	_aRobots, Reasoning, and Reification _h[electronic resource] / _cby James P. Gunderson, Louise F. Gunderson.
264		1	_aBoston, MA : _bSpringer US, _c2009.
300			_aXVI, 208p. 181 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aSome background material on probability and biology -- Using Cognition and Physiology to Build a Cognitive Model -- Representation -- Perception/Action System -- Design of a Reification Engine -- Bridging the Sensor to Symbol Gap -- Working Memory and the Construction of Personal Experiences -- Semantic Memory and the Personal Rough Ontology -- Deliberative System -- Putting it All Together -- Testing -- Where do we go from here.
520			_aRobots, Reasoning, and Reification focuses on a critical obstacle that is preventing the development of intelligent, autonomous robots:the gap between the ability to reason about the world and the ability to sense the world and translate that sensory data into a symbolic model. This ability is what enables living systems to look at the world and perceive the things in it. In addition, intelligent living systems can extrapolate from their mental models and predict the effects of their actions in the real world. The authors call this bi-directional mapping of sensor data to symbols and symbolic manipulation onto real world effects reification. After exploring the gulf between bottom-up and top-down approaches to autonomous robotics, the book develops the concepts of reification from biologically based premises, and follows the development into the necessary components and structures that can be used to provide equivalent capabilities for intelligent robots. It continues by demonstrating how the reification engine supports both learning from experience and creating new behaviors and representations of the world.
650		0	_aCOMPUTER SCIENCE.
650		0	_aARTIFICIAL INTELLIGENCE.
650	1	4	_aCOMPUTER SCIENCE.
650	2	4	_aARTIFICIAL INTELLIGENCE (INCL. ROBOTICS).
700	1		_aGunderson, Louise F. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387874876
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-87488-3 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SCS
942			_2ddc _cER
999			_c59310 _d59310