![Advances in Robot Learning [electronic resource] : 8th European Workshop on Learning Robots, EWLR-8 Lausanne, Switzerland, September 18, 1999 Proceedings /](/search/themes/bootstrap3/images/libros.png)
Advances in Robot Learning [electronic resource] : 8th European Workshop on Learning Robots, EWLR-8 Lausanne, Switzerland, September 18, 1999 Proceedings /
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 Mobile Robots.
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| Main Authors: | , , |
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| Format: | Texto biblioteca |
| Language: | eng |
| Published: |
Berlin, Heidelberg : Springer Berlin Heidelberg,
2000
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| Subjects: | Computer science., Artificial intelligence., Computer simulation., Control engineering., Robotics., Mechatronics., Automation., Computer Science., Artificial Intelligence (incl. Robotics)., Robotics and Automation., Simulation and Modeling., Control, Robotics, Mechatronics., |
| Online Access: | http://dx.doi.org/10.1007/3-540-40044-3 |
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| Summary: | 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 Mobile Robots. |
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