Abstract
We describe the implementation and testing of the kins multi-strategy learning controller for real mobile robot navigation. This controller uses low-level reactive control that is modulated on-line by a learning system based on case-based reasoning and reinforcement learning. The case-based reasoning part captures regularities in the environment. The reinforcement learning part gradually improves the acquired knowledge. Evaluation of the controller is presented in a real and in a realistic simulated mobile robot, across different types of environments.
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© 1998 Springer-Verlag Berlin Heidelberg
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Chagas, N.C., Hallam, J. (1998). A Learning Mobile Robot: Theory, Simulation and Practice. In: Birk, A., Demiris, J. (eds) Learning Robots. EWLR 1997. Lecture Notes in Computer Science(), vol 1545. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49240-2_10
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DOI: https://doi.org/10.1007/3-540-49240-2_10
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