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Reinforcement Learning

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Part of the book series: Undergraduate Topics in Computer Science ((UTICS))

Abstract

The challenging task of autonomously learning skills without the help of a teacher, solely based on feedback from the environment to actions, is called reinforcement learning. Still being an active area of research, some impressive results can be shown on robots. Reinforcement learning enables robots to learn motor skills as well as simple cognitive behavior. We use a simple robot with only two degrees of freedom to demonstrate the strengths of the value iteration and Q-learning algorithms, as well as their limitations.

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Notes

  1. 1.

    The arm movement space consisting of arcs is rendered as a right-angled grid.

  2. 2.

    Further information and related sources about crawling robots are available through www.hs-weingarten.de/~ertel/kibuch.

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Correspondence to Wolfgang Ertel .

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Ertel, W. (2017). Reinforcement Learning. In: Introduction to Artificial Intelligence. Undergraduate Topics in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-58487-4_10

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  • DOI: https://doi.org/10.1007/978-3-319-58487-4_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-58486-7

  • Online ISBN: 978-3-319-58487-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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