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  • © 2010

Qualitative Spatial Abstraction in Reinforcement Learning

Authors:

  • Book introduces many original ideas
  • Significant contribution to the field of reinforcement learning
  • Contains pointers to future research

Part of the book series: Cognitive Technologies (COGTECH)

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xvii
  2. Introduction

    • Lutz Frommberger
    Pages 1-8
  3. Foundations of Reinforcement Learning

    • Lutz Frommberger
    Pages 9-21
  4. Qualitative State Space Abstraction

    • Lutz Frommberger
    Pages 43-65
  5. Empirical Evaluation

    • Lutz Frommberger
    Pages 123-154
  6. Summary and Outlook

    • Lutz Frommberger
    Pages 155-159
  7. Back Matter

    Pages 161-174

About this book

Reinforcement learning has developed as a successful learning approach for domains that are not fully understood and that are too complex to be described in closed form. However, reinforcement learning does not scale well to large and continuous problems. Furthermore, acquired knowledge specific to the learned task, and transfer of knowledge to new tasks is crucial.

 

In this book the author investigates whether deficiencies of reinforcement learning can be overcome by suitable abstraction methods. He discusses various forms of spatial abstraction, in particular qualitative abstraction, a form of representing knowledge that has been thoroughly investigated and successfully applied in spatial cognition research. With his approach, he exploits spatial structures and structural similarity to support the learning process by abstracting from less important features and stressing the essential ones. The author demonstrates his learning approach and the transferability of knowledge by having his system learn in a virtual robot simulation system and consequently transfer the acquired knowledge to a physical robot. The approach is influenced by findings from cognitive science.

 

The book is suitable for researchers working in artificial intelligence, in particular knowledge representation, learning, spatial cognition, and robotics.

 

Authors and Affiliations

  • Cognitive Systems Group, Department of Mathematics, University of Bremen, Bremen, Germany

    Lutz Frommberger

About the author

Dr. Frommberger is a researcher in the Cognitive Systems Research Group (SFB/TR 8 Spatial Cognition) of Universität Bremen; his special areas of expertise are spatial abstraction techniques, efficient reinforcement learning, cognitive logistics and qualitative representations of space.

Bibliographic Information

  • Book Title: Qualitative Spatial Abstraction in Reinforcement Learning

  • Authors: Lutz Frommberger

  • Series Title: Cognitive Technologies

  • DOI: https://doi.org/10.1007/978-3-642-16590-0

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2010

  • Hardcover ISBN: 978-3-642-16589-4Published: 12 November 2010

  • Softcover ISBN: 978-3-642-26600-3Published: 02 January 2013

  • eBook ISBN: 978-3-642-16590-0Published: 13 December 2010

  • Series ISSN: 1611-2482

  • Series E-ISSN: 2197-6635

  • Edition Number: 1

  • Number of Pages: XVII, 174

  • Topics: Artificial Intelligence, Control, Robotics, Mechatronics

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access