Neuroscience-Inspired Dynamic Architectures

نویسندگان

  • Catherine D. Schuman
  • Douglas Birdwell
  • Mark Dean
چکیده

Neuroscience-inspired computational elements and architectures are one of the most popular ideas for replacing the von Neumann architecture. In this work, we propose a neuroscience-inspired dynamic architecture (NIDA) and discuss a method for automatically designing NIDA networks to accomplish tasks. We discuss the reasons we chose evolutionary optimization as the main design method and propose future directions for the

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تاریخ انتشار 2016