Advances in Robot Learning

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.

Includes supplementary material: sn.pub/extras