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Lutz Frommberger - Qualitative Spatial Abstraction for Reinforcement Learning - 9783642165894 - V9783642165894
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Qualitative Spatial Abstraction for Reinforcement Learning

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Description for Qualitative Spatial Abstraction for Reinforcement Learning Hardback. Reinforcement learning has evolved to tackle domains that are yet to be fully understood, or are too complex for a closed description. In this book the author investigates whether suitable abstraction methods can overcome the discipline's deficiencies. Series: Cognitive Technologies. Num Pages: 174 pages, biography. BIC Classification: TJFM; UYQM. Category: (P) Professional & Vocational. Dimension: 239 x 161 x 17. Weight in Grams: 446.

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 ... Read more

 

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

 

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Product Details

Format
Hardback
Publication date
2010
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
174
Condition
New
Series
Cognitive Technologies
Number of Pages
174
Place of Publication
Berlin, Germany
ISBN
9783642165894
SKU
V9783642165894
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

About Lutz Frommberger
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.

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