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A Reverse Genetic Approach to Test Functional Redundancy During Embryogenesis
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Advancing System Performance with Redundancy: From Biological to Artificial Designs.

Anh Tuan Nguyen1, Jian Xu2, Diu Khue Luu3

  • 1Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, U.S.A. nguy2833@umn.edu.

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|January 16, 2019
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Summary

Biological systems use redundancy not just for fault tolerance, but also to enhance accuracy. This study introduces representational redundancy (RPR) and entangled redundancy (ETR) to explain this phenomenon in systems like human vision and deep neural networks.

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Area of Science:

  • Biological Systems
  • Artificial Intelligence
  • Systems Theory

Background:

  • Redundancy is a key feature in biological systems (e.g., genetic, visual, muscular, nervous systems) but its mechanisms are not fully understood.
  • Traditionally, redundancy has been viewed primarily for fault tolerance in both biological and artificial systems.
  • Previous work demonstrated redundancy engineered for enhanced accuracy and precision, inspired by human binocular vision.

Purpose of the Study:

  • To present a unified theory explaining how redundancy can enhance accuracy and precision.
  • To introduce two complementary mechanisms: representational redundancy (RPR) and entangled redundancy (ETR).
  • To identify biological and artificial examples illustrating the application of this theory.

Main Methods:

  • Development of a unified theoretical framework for redundancy utilization.
  • Analysis of representational redundancy (RPR) and entangled redundancy (ETR).
  • Application of the theory to explain performance in the human musculoskeletal system (HMS) and deep residual neural networks (ResNet).

Main Results:

  • A novel theory is proposed for how redundancy enhances system accuracy and precision.
  • Two distinct mechanisms, RPR and ETR, are identified as drivers of this enhanced performance.
  • The theory successfully explains superior performance in both biological (HMS) and artificial (ResNet) systems.

Conclusions:

  • Redundancy offers a mechanism beyond fault tolerance for improving system accuracy and precision.
  • The proposed theory of RPR and ETR provides a new lens for understanding biological and artificial systems.
  • This framework can guide the development of bio-inspired redundant artificial systems and advance the study of biological mechanisms.