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.