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Record Nr. |
UNINA9910143631303321 |
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Titolo |
Advances in Robot Learning : 8th European Workhop on Learning Robots, EWLR-8 Lausanne, Switzerland, September 18, 1999 Proceedings / / edited by Jeremy Wyatt, John Demiris |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2000 |
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ISBN |
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Edizione |
[1st ed. 2000.] |
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Descrizione fisica |
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1 online resource (VIII, 172 p.) |
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Collana |
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Lecture Notes in Artificial Intelligence ; ; 1812 |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Robotics |
Automation |
Computer simulation |
Automatic control |
Mechatronics |
Artificial Intelligence |
Robotics and Automation |
Simulation and Modeling |
Control, Robotics, Mechatronics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters and index. |
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Nota di contenuto |
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Map 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 |
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Sommario/riassunto |
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This 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. |
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