LEADER 01693nam 2200421Ia 450 001 996386459603316 005 20221108021603.0 035 $a(CKB)4940000000078316 035 $a(EEBO)2241008842 035 $a(OCoLC)12648217 035 $a(EXLCZ)994940000000078316 100 $a19851008d1679 uy | 101 0 $aeng 135 $aurbn||||a|bb| 200 10$a1679, a yea and nay almanack for the people called by much of the world Quakers$b[electronic resource] $econtaining many needfull and necessary observations from the first day of the first month, till the last day of the twelfth month, a being the third after the bissextile or the leaping year : calculated properly for the meridian of the Bull and Mouth within Aldersgate, and may indifferently serve for any other meeting-house what or wheresoever 210 $aLondon $cPrinted for the Company of Stationers$d1679 215 $a[48] p 300 $aReproduction of original in Bodleian Library. 300 $aAttributed to William Winstanley by Wing. 300 $a"The second part of the yea and nay almanack" has separate t.p. 300 $aAdvertisement: p. [48] 330 $aeebo-0014 606 $aAlmanacs, English 606 $aAstrology$vEarly works to 1800 606 $aEphemerides 615 0$aAlmanacs, English. 615 0$aAstrology 615 0$aEphemerides. 700 $aWinstanley$b William$f1628?-1698.$0790994 801 0$bEAA 801 1$bEAA 801 2$bOCL 801 2$bUMI 801 2$bWaOLN 906 $aBOOK 912 $a996386459603316 996 $a1679, a yea and nay almanack for the people called by much of the world Quakers$92402994 997 $aUNISA LEADER 03277nam 22006375 450 001 9910736004703321 005 20230801002656.0 010 $a3-031-37832-6 024 7 $a10.1007/978-3-031-37832-4 035 $a(MiAaPQ)EBC30670671 035 $a(Au-PeEL)EBL30670671 035 $a(DE-He213)978-3-031-37832-4 035 $a(PPN)272260487 035 $a(CKB)27899796500041 035 $a(EXLCZ)9927899796500041 100 $a20230801d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aInductive Biases in Machine Learning for Robotics and Control /$fby Michael Lutter 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (131 pages) 225 1 $aSpringer Tracts in Advanced Robotics,$x1610-742X ;$v156 311 08$aPrint version: Lutter, Michael Inductive Biases in Machine Learning for Robotics and Control Cham : Springer,c2023 9783031378317 327 $aIntroduction -- A Differentiable Newton-Euler Algorithm for Real-World Robotics -- Combining Physics and Deep Learning for Continuous-Time Dynamics Models -- Continuous-Time Fitted Value Iteration for Robust Policies -- Conclusion. 330 $aOne important robotics problem is ?How can one program a robot to perform a task?? Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot learning solely relies on black-box models and data. This book shows that these two approaches of classical engineering and black-box machine learning are not mutually exclusive. To solve tasks with robots, one can transfer insights from classical robotics to deep networks and obtain better learning algorithms for robotics and control. To highlight that incorporating existing knowledge as inductive biases in machine learning algorithms improves performance, this book covers different approaches for learning dynamics models and learning robust control policies. The presented algorithms leverage the knowledge of Newtonian Mechanics, Lagrangian Mechanics as well as the Hamilton-Jacobi-Isaacs differential equation as inductive bias and are evaluated on physical robots. 410 0$aSpringer Tracts in Advanced Robotics,$x1610-742X ;$v156 606 $aAutomatic control 606 $aRobotics 606 $aAutomation 606 $aComputational intelligence 606 $aControl, Robotics, Automation 606 $aComputational Intelligence 606 $aRobotics 606 $aControl and Systems Theory 615 0$aAutomatic control. 615 0$aRobotics. 615 0$aAutomation. 615 0$aComputational intelligence. 615 14$aControl, Robotics, Automation. 615 24$aComputational Intelligence. 615 24$aRobotics. 615 24$aControl and Systems Theory. 676 $a629.8 676 $a629.892 700 $aLutter$b Michael$01380476 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910736004703321 996 $aInductive Biases in Machine Learning for Robotics and Control$93421911 997 $aUNINA