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Automatic Car Parking: A Reinforcement Learning Approach

  • Darío Maravall
  • Miguel Ángel Patricio
  • Javier de Lope
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2686)

Abstract

The automatic parking of a car-like robot is the problem considered in this paper to evaluate the role played by formal representations and models in neural-based controllers. First, a model-free control scheme is introduced. The respective control actions are sensory-based and consist of a dynamic, neural-based process in which the neurocontroller optimizes ad hoc performance functions. Afterwards, a model-based neurocontroller that builds without supervised a formal representation of its interaction with the environment is proposed. The resulting model is eventually utilized to generate the control actions. Simulated experimentation has shown that there is an improvement in robot behavior when a model is used, at the cost of higher complexity and computational load.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Darío Maravall
    • 1
  • Miguel Ángel Patricio
    • 2
  • Javier de Lope
    • 1
  1. 1.Department of Artificial Intelligence Faculty of Computer ScienceUniversidad Politécnica de MadridMadridSpain
  2. 2.Departamento de InformáticaUniversidad Carlos III de MadridMadrid

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