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Emergent Neural Computational Architectures Based on Neuroscience pp 98–113Cite as

Modularity and Specialized Learning: Mapping between Agent Architectures and Brain Organization

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2036))

Abstract

This volume is intended to help advance the field of artificial neural networks along the lines of complexity present in animal brains. In particular, we are interested in examining the biological phenomena of modularity and specialized learning. These topics are already the subject of research in another area of artificial intelligence. The design of complete autonomous agents (CAA), such as mobile robots or virtual reality characters, has been dominated by modular architectures and context-driven action selection and learning. In this chapter, we help bridge the gap from neuroscience to artificial neural networks (ANN) by incorporating CAA. We do this both directly, by using CAA as a metaphor to consider requirements for ANN, and indirectly, by using CAA research to better understand and model neuroscience. We discuss the strengths and the limitations of these forms of modeling, and propose as future work extensions to CAA inspired by neuroscience.

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Author information

Authors and Affiliations

  1. Artificial Intelligence Laboratory, MIT, 545 Technology Square, Cambridge, MA, 02139, USA

    Joanna Bryson & Lynn Andrea Stein

Authors
  1. Joanna Bryson
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  2. Lynn Andrea Stein
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Editors and Affiliations

  1. Centre of Informatics, SCET, University of Sunderland, St PetersWay, Sunderland SR6 0DD, UK

    Stefan Wermter

  2. Department of Computer Science, University of York, York, Y010 5DD, UK

    Jim Austin

  3. Institute for Adaptive and Neural Computation, University of Edinburgh, 5 Forrest Hill, Edinburgh, UK

    David Willshaw

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© 2001 Springer-Verlag Berlin Heidelberg

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Bryson, J., Stein, L.A. (2001). Modularity and Specialized Learning: Mapping between Agent Architectures and Brain Organization. In: Wermter, S., Austin, J., Willshaw, D. (eds) Emergent Neural Computational Architectures Based on Neuroscience. Lecture Notes in Computer Science(), vol 2036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44597-8_7

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  • DOI: https://doi.org/10.1007/3-540-44597-8_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42363-8

  • Online ISBN: 978-3-540-44597-5

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