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Million module neural systems evolution

The next step in ATR's billion neuron artificial brain (“CAM-Brain”) project

  • Evolvable Hardware and Robotics
  • Conference paper
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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1363))

Abstract

This position paper discusses the evolution of multi-module neural net systems, where the number of neural net modules is up to ten million (i.e. an “artificial brain”). ATR's “CAM-Brain” Project [de Garis 1993, 1996] has progressed to the point where it is technically possible (using a new FPGA (Field Programmable Gate Array) based evolvable hardware (EHW or E-Hard) system to be completed by the spring of 1998 [Korkin & de Garis 1997]) to begin to evolve and build an artificial brain containing 10,000 neural net modules. This development raises the prospect that within a few years these numbers will rapidly increase. This paper introduces some issues that such massive system-building will generate. The immediate question is “What should we evolve?” This paper presents some suggested evolvable system targets containing N neural net modules, where N = 100; 1000; 10,000; 100,000; 1,000,000; 10,000,000 with an emphasis on the N = 100 case, for purposes of illustration. The issues involved are not only of a conceptual and evolutionary engineering nature, but (when N is large) economic, managerial and even political as well.

Note : de Garis papers can be found at site :- http://www.hip.atr.co.jp/-degaris

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References

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Jin-Kao Hao Evelyne Lutton Edmund Ronald Marc Schoenauer Dominique Snyers

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© 1998 Springer-Verlag Berlin Heidelberg

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de Garis, H., Kang, L., He, Q., Pan, Z., Ootani, M., Ronald, E. (1998). Million module neural systems evolution. In: Hao, JK., Lutton, E., Ronald, E., Schoenauer, M., Snyers, D. (eds) Artificial Evolution. AE 1997. Lecture Notes in Computer Science, vol 1363. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0026611

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  • DOI: https://doi.org/10.1007/BFb0026611

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64169-8

  • Online ISBN: 978-3-540-69698-8

  • eBook Packages: Springer Book Archive

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