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001 978-3-319-03194-1
003 DE-He213
005 20200421112051.0
007 cr nn 008mamaa
008 131123s2014 gw | s |||| 0|eng d
020 _a9783319031941
_9978-3-319-03194-1
024 7 _a10.1007/978-3-319-03194-1
_2doi
050 4 _aTJ210.2-211.495
050 4 _aT59.5
072 7 _aTJFM1
_2bicssc
072 7 _aTEC037000
_2bisacsh
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.892
_223
100 1 _aKober, Jens.
_eauthor.
245 1 0 _aLearning Motor Skills
_h[electronic resource] :
_bFrom Algorithms to Robot Experiments /
_cby Jens Kober, Jan Peters.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXVI, 191 p. 56 illus., 54 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Tracts in Advanced Robotics,
_x1610-7438 ;
_v97
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.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aRobotics.
650 0 _aAutomation.
650 1 4 _aEngineering.
650 2 4 _aRobotics and Automation.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aPeters, Jan.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319031934
830 0 _aSpringer Tracts in Advanced Robotics,
_x1610-7438 ;
_v97
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-03194-1
912 _aZDB-2-ENG
942 _cEBK
999 _c57231
_d57231