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Biologically Inspired Framework for Learning and Abstract Representation of Attention Control

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Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint (WAPCV 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4840))

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Abstract

The goal of this research is to develop a framework that enables artificial agents to learn active control of their attention as a means toward efficient planning, decision-making, and recognition. The proposed method is inspired by recent findings in psychology and neuroscience that give rise to the assumption that sequential firing of mirror neurons are connected with prediction, recognition, and planning. As these capabilities are connected to active perception, we hypothesize that simulated sequential mirror neurons can provide an abstract representation of learned attention control.

The proposed framework consists of three phases. The first phase is designed for learning active control of attention using reinforcement learning. In the second phase, sequential concepts are extracted from the agent’s experience and sequential mirror neurons are generated. In the last phase the concepts represented by these sequential mirror neurons are employed for higher level motor-planning and control of attention, as well as recognition.

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Author information

Authors and Affiliations

  1. AI and Robotics Lab, Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Iran

    Hadi Fatemi Shariatpanahi & Majid Nili Ahmadabadi

  2. School of Cognitive Sciences, IPM, Tehran, Iran

    Majid Nili Ahmadabadi

Authors
  1. Hadi Fatemi Shariatpanahi
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  2. Majid Nili Ahmadabadi
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Editor information

Editors and Affiliations

  1. Joanneum Research, Forschungsgesellschaft mbH, Computational Perception Group,, Institute of Digital Image Processing, Wastiangasse 6, 8010, Graz, Austria

    Lucas Paletta

  2. Autonomous Intelligent Systems (AIS), Autonomous Robots Department, Fraunhofer Institute, Schloss Birlinghoven, 53754, Sankt Augustin, Germany

    Erich Rome

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© 2007 Springer-Verlag Berlin Heidelberg

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Fatemi Shariatpanahi, H., Nili Ahmadabadi, M. (2007). Biologically Inspired Framework for Learning and Abstract Representation of Attention Control. In: Paletta, L., Rome, E. (eds) Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint. WAPCV 2007. Lecture Notes in Computer Science(), vol 4840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77343-6_20

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  • DOI: https://doi.org/10.1007/978-3-540-77343-6_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77342-9

  • Online ISBN: 978-3-540-77343-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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