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An Algorithmic Approach to Natural Behavior.

Andrew M Hein1, Douglas L Altshuler2, David E Cade3

  • 1Southwest Fisheries Science Center, National Oceanic and Atmospheric Administration, Santa Cruz, CA 95060, USA; Institute of Marine Sciences, University of California, Santa Cruz, CA 95060, USA; Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95060, USA.

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|June 10, 2020
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Summary
This summary is machine-generated.

Researchers are uncovering general principles of natural animal behavior by studying pursuit and evasion. Simple rules, called behavioral algorithms, link sensory input to motor output, providing insights into complex actions.

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Area of Science:

  • Behavioral biology
  • Neuroscience
  • Computational modeling

Background:

  • Understanding natural animal behavior is complex due to its diversity and multi-scale nature.
  • Pursuit and evasion behaviors offer tractable systems for studying general control principles.

Purpose of the Study:

  • To review studies on animal pursuit and evasion to uncover general control principles of natural behavior.
  • To advocate for an algorithmic approach to studying behavior, linking sensory input to motor output.

Main Methods:

  • Review of theory-driven experiments and modeling techniques in animal pursuit and evasion.
  • Identification and mathematical characterization of behavioral algorithms.

Main Results:

  • Complex pursuit and evasion behaviors can arise from simple, repeatable rules (behavioral algorithms).
  • Discovery of predator guidance rules for prey interception and collision avoidance mechanisms.

Conclusions:

  • Behavioral algorithms provide a foundational approach for studying natural behavior more broadly.
  • An algorithmic perspective facilitates exploration of both neural implementation and ecological outcomes of behavior.