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Combining Attention and Value Maps

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Artificial Neural Networks: Biological Inspirations – ICANN 2005 (ICANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3696))

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Abstract

We present an approach where we combine attention with value maps for the purpose of acquiring a decision-making policy for multiple concurrent goals. The former component is essential for dealing with an uncertain and open environment while the latter offers a general model for building decision-making systems based on reward information. We discuss the multiple goals policy acquisition problem and justify our approach. We provide simulation results that support our solution.

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References

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Author information

Authors and Affiliations

  1. Foundation for Research and Technology – Hellas, Institute of Computer Science, Vassilika Vouton, P.O. Box 1385, 711 10, Heraklion, Greece

    Stathis Kasderidis

  2. Dept. of Mathematics, King’s College, Strand, London, WC2R 2LS, UK

    John G. Taylor

Authors
  1. Stathis Kasderidis
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  2. John G. Taylor
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Editor information

Editors and Affiliations

  1. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  2. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01–447, Warsaw, Poland

    Janusz Kacprzyk

  3. Adaptive Informatics Research Centre, Helsinki University of Technology, P.O. Box 5400, 02015 HUT, Finland

    Erkki Oja

  4. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Sławomir Zadrożny

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© 2005 Springer-Verlag Berlin Heidelberg

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Kasderidis, S., Taylor, J.G. (2005). Combining Attention and Value Maps. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_13

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  • DOI: https://doi.org/10.1007/11550822_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28752-0

  • Online ISBN: 978-3-540-28754-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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