000			02951nam a22003855i 4500
001			293960
003			MX-SnUAN
005			20170705134229.0
007			cr nn 008mamaa
008			150903s2014 gw | o |||| 0|eng d
020			_a9783319031941 _99783319031941
024	7		_a10.1007/9783319031941 _2doi
035			_avtls000346371
039		9	_a201509030916 _bVLOAD _c201405050334 _dVLOAD _y201402070856 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aTJ210.2-211.495
100	1		_aKober, Jens. _eautor _9327092
245	1	0	_aLearning Motor Skills : _bFrom Algorithms to Robot Experiments / _cby Jens Kober, Jan Peters.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2014.
300			_axvI, 191 páginas 56 ilustraciones, 54 ilustraciones en color. _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aSpringer Tracts in Advanced Robotics, _x1610-7438 ; _v97
500			_aSpringer eBooks
505	0		_aReinforcement Learning in Robotics: A Survey -- Movement Templates for Learning of Hitting and Batting -- Policy Search for Motor Primitives in Robotics -- Reinforcement Learning to Adjust Parameterized Motor Primitives to New Situations -- Learning Prioritized Control of Motor Primitives.
520			_aThis book presents the state of the art in reinforcement learning applied to robotics both in terms of novel algorithms and applications. It discusses recent approaches that allow robots to learn motor skills and presents tasks that need to take into account the dynamic behavior of the robot and its environment, where a kinematic movement plan is not sufficient. The book illustrates a method that learns to generalize parameterized motor plans which is obtained by imitation or reinforcement learning, by adapting a small set of global parameters, and appropriate kernel-based reinforcement learning algorithms. The presented applications explore highly dynamic tasks and exhibit a very efficient learning process. All proposed approaches have been extensively validated with benchmarks tasks, in simulation, and on real robots. These tasks correspond to sports and games but the presented techniques are also applicable to more mundane household tasks. The book is based on the first author’s doctoral thesis, which won the 2013 EURON Georges Giralt PhD Award.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aPeters, Jan. _eautor _9327093
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783319031934
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-319-03194-1 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c293960 _d293960