The proposal of this work involves a simulation of an ant colony swarm that was applied to a problem of search and rescue of objects of interest.
An evolutionary algorithm was implemented to optimize the ant swarm parameters in order to improve performance on the colony goal.
Hardware acceleration in CUDA and OpenGL provides the system with the ability to simulate a large number of agents simultaneously, in order to study the relevance of swarm size in the performance of a task objective.
Step 1: clone this repository with git clone https://github.com/matheuslosilva/Hardware-Accelerated-Ant-Colony-Based-Swarm-System --recursive
Step 2: Download the following dependencies
GLFW (window calls) - GLM (math calls): https://www.glfw.org/download sudo apt-get install libglfw3-dev libglm-dev
Step 3: change the current directory with cd Hardware-Accelerated-Ant-Colony-Based-Swarm-System
Step 4: run make
Step 5: run make run
OpenGL and CUDA references used:
https://github.com/JoeyDeVries/LearnOpenGL
https://github.com/VictorGordan/opengl-tutorials