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Genetic algorithms produce individual robotic rat pup behaviors that match Norway rat pup behaviors at multiple scales

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Abstract

We designed input/output cognitive architectures for individual robotic rat pups using genetic algorithms with the aim of achieving insight into Norway rat pup behavior. Our cognitive architectures were evolved using only metrics of Norway rat pup macro-behavior (e.g., percent of time spent in corners, along walls, and center of an arena during animal experiments). Robotic rat pups not only quantitatively matched Norway rat pups at the macro-level (by design), but additionally qualitatively matched Norway rat pup behavior at the micro-behavior scales (corner- snooping, punting). The complexity of the resulting deterministic input–output controllers may lend support to previous studies that show random-like control codes (possibly emerging from complex underlying input–output interactions, or brain-initiated spontaneous behavior) can produce apparently realistic rat pup behavior below a certain age.

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Acknowledgments

This work was supported by the U.S. National Science Foundation under Grant No. 0218927 and by the U.S. National Institutes of Health under Grant 5R01MH065555. We thank I. Skavhaug for technical assistance with the manuscript figures and for helpful suggestions.

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Authors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, University of California, Davis, USA

    Chris Sullivan & Sanjay S. Joshi

  2. Department of Computer Science and Engineering, University of California, Davis, USA

    Ryan Loughlin

  3. Department of Psychology, University of California, Davis, USA

    Jeffrey C. Schank

Authors
  1. Chris Sullivan
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  2. Ryan Loughlin
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  3. Jeffrey C. Schank
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  4. Sanjay S. Joshi
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Corresponding author

Correspondence to Sanjay S. Joshi.

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Sullivan, C., Loughlin, R., Schank, J.C. et al. Genetic algorithms produce individual robotic rat pup behaviors that match Norway rat pup behaviors at multiple scales. Artif Life Robotics 20, 93–102 (2015). https://doi.org/10.1007/s10015-015-0208-y

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  • DOI: https://doi.org/10.1007/s10015-015-0208-y

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