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Schooling model optimised by evolution in presence of live predators

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[1] adapts one of the most influential models in the field of collective behaviour [2], and projects virtual prey in the tank of a bluegill sunfish (Lepomis macrochirus). Based on predatory interactions of the sunfish with virtual prey, virtual agents evolve social interaction rules. The experiment depicts the importance of both alignment with and attraction to conspecifics to avoid predators (even in a condition where prey are not responding to the predator). Here, we present this simulation with the evolvable parameters set to their optimum.

The simulation was written in C++ and uses OpenCV for visualisation.

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The above code is written using C++11 and tested on MacOS Sierra 10.12.5. The visualisation is executed using OpenCV 3.2.0. In case of troubles installing OpenCV / linking it to the C++ project, visualisation can be turned off by silencing OpenCV headers and the graphics function in main.cpp. The rest of the code should still work on naked C++.

Reference

  1. Christos C. Ioannou, Vishwesha Guttal, and Iain D. Couzin, Predatory fish select for coordinated collective motion in virtual prey, Science 337, 1212 (2017).

  2. Iain D. Couzin, Jens Krause, Nigel R. Franks, and Simon A. Levin, Effective leadership and decision-making in animal groups on the move, Nature 433, 513 (2005).

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Schooling model optimised by evolution in presence of live predators

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