title: |
Economic Attention Networks: Associative Memory and Resource Allocation for General Intelligence |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
ISBN: |
978-90-78677-24-6 | |
DOI: |
doi:10.2991/agi.2009.19 (how to use a DOI) | |
author(s): |
Joel Pitt, Matthew Ikle, George Sellmann, Ben Goertzel |
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publication date: |
May 2009 |
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abstract: |
A novel method for simultaneously storing memories and
allocating resources in AI systems is presented. The
method, Economic Attention Networks (ECANs), bears
some resemblance to the spread of activation in attractor
neural networks, but differs via explicitly differentiating two
kinds of "activation" (Short Term Importance, related to
processor allocation; and Long Term Importance, related to
memory allocation), and in using equations that are based
on ideas from economics rather than approximative neural
modeling. Here we explain the basic ideas of ECANs, and
then investigate the functionality of ECANs as associative
memories, via mathematical analysis and the reportage of
experimental results obtained from the implementation of
ECANs in the OpenCog integrative AGI system.
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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |