LEADER 04210nam 22007575 450 001 9910143631303321 005 20251116234013.0 010 $a3-540-40044-3 024 7 $a10.1007/3-540-40044-3 035 $a(CKB)1000000000211242 035 $a(SSID)ssj0000321019 035 $a(PQKBManifestationID)11246883 035 $a(PQKBTitleCode)TC0000321019 035 $a(PQKBWorkID)10276812 035 $a(PQKB)10558662 035 $a(DE-He213)978-3-540-40044-8 035 $a(MiAaPQ)EBC3072774 035 $a(PPN)155215469 035 $a(BIP)13626930 035 $a(BIP)6997509 035 $a(EXLCZ)991000000000211242 100 $a20121227d2000 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAdvances in Robot Learning $e8th European Workhop on Learning Robots, EWLR-8 Lausanne, Switzerland, September 18, 1999 Proceedings /$fedited by Jeremy Wyatt, John Demiris 205 $a1st ed. 2000. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2000. 215 $a1 online resource (VIII, 172 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v1812 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-540-41162-3 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aMap Building through Self-Organisation for Robot Navigation -- Learning a Navigation Task in Changing Environments by Multi-task Reinforcement Learning -- Toward Seamless Transfer from Simulated to Real Worlds: A Dynamically?Rearranging Neural Network Approach -- How Does a Robot Find Redundancy by Itself? -- Learning Robot Control by Relational Concept Induction with Iteratively Collected Examples -- Reinforcement Learning in Situated Agents: Theoretical Problems and Practical Solutions -- A Planning Map for Mobile Robots: Speed Control and Paths Finding in a Changing Environment -- Probabilistic and Count Methods in Map Building for Autonomous Mobile Robots -- Biologically-Inspired Visual Landmark Learning for Mobile Robots. 330 $aThis book constitutes the thoroughly refereed post-workshop proceedings of the 8th European Workshop on Learning Robots, EWLR'99, held in Lausanne, Switzerland in September 1999.The seven revised full workshop papers presented were carefully reviewed and selected for inclusion in the book. Also included are two invited full papers. Among the topics addressed are map building for robot navigation, multi-task reinforcement learning, neural network approaches, example-based learning, situated agents, planning maps for mobile robots, path finding, autonomous robots, and biologically inspired approaches. 410 0$aLecture Notes in Artificial Intelligence ;$v1812 606 $aArtificial intelligence 606 $aRobotics 606 $aAutomation 606 $aComputer simulation 606 $aAutomatic control 606 $aMechatronics 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aRobotics and Automation$3https://scigraph.springernature.com/ontologies/product-market-codes/T19020 606 $aSimulation and Modeling$3https://scigraph.springernature.com/ontologies/product-market-codes/I19000 606 $aControl, Robotics, Mechatronics$3https://scigraph.springernature.com/ontologies/product-market-codes/T19000 615 0$aArtificial intelligence. 615 0$aRobotics. 615 0$aAutomation. 615 0$aComputer simulation. 615 0$aAutomatic control. 615 0$aMechatronics. 615 14$aArtificial Intelligence. 615 24$aRobotics and Automation. 615 24$aSimulation and Modeling. 615 24$aControl, Robotics, Mechatronics. 676 $a629.8/9263 702 $aWyatt$b J$g(Jeremy),$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aDemiris$b John$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aEuropean Workshop on Learning Robots. 906 $aBOOK 912 $a9910143631303321 996 $aAdvances in Robot Learning$91980336 997 $aUNINA