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This is part of the TU Delft Research Project. It serves as a way to recreate the results described in the paper Protection algorithms using fault resilient fish swarming behaviour.

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Fish Swarming Behaviour

This is part of the TU Delft Research Project. It serves as a way to recreate the results described in the paper Protection algorithms using fault resilient fish swarming behaviour.

Libraries

pygame : pip install pygame

colorsys : pip install colorsys


Prey Predator

To run this instance:

  • With custom weights:

python preyPredator/preyPredator.py -b {FAULTY_BOIDS} -p {FAULTY_PREDATORS}

  • With the default weights:

python preyPredator/preyPredator.py

To use the genetic algorithm for weight training:

python script/training_script.py


Missile Target

  • With custom weights:

python preyPredator/missileTarget.py -b {FLEE_WEIGHT} -p {PROTECT_WEIGHT}

  • With the default weights:

python preyPredator/missileTarget.py


Results

To generate the graphs for each instance:

  • Run the runner script for that instance:

python scrips/preyPredator_runner.py

python scrips/rocketTarget_runner.py

  • Run the plotting script for that instance:

python plotting/plotPreyPredator.py

python plotting/plotRocketTarget.py

  • The results are firstly generated in the results folder and then plotted

Other remarks

  • All weights and constants can be modified in the constants file of each instance
  • Training instances can also be run individually using:

python preyPredator/geneticsTraining.py

About

This is part of the TU Delft Research Project. It serves as a way to recreate the results described in the paper Protection algorithms using fault resilient fish swarming behaviour.

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