A.I. Ant Colony project
Nominated for European Design Awards 2023
Category Digital Installations
Every day, we rely on algorithms that solve complex problems and efficiently execute tasks. Some real-life examples are optimizing traffic lights or public transport schedules. In this project, we created a visual experience showing the multiple levels of decision-making driven by algorithms so you could ‘see’ how an algorithm works.
We wanted to visualize a complex algorithm that mimics nature and bridges abstract technology and the real world. We chose an Ant Colony Optimization (ACO) algorithm to bring our idea to life. The ACO algorithm imitates the behavior of ants seeking a path between their colony and food source and is used to solve optimization problems.
The final result is a digital art installation that visualizes the complexity of a running Ant Colony that tries to find the shortest route between natural resources, in this case, all parks in Chicago. To have ants walk the streets of the city, we created a high-resolution digital map. Using data from OpenStreetMaps, we color-coded places in each individual park.
Our visualization software ensured Ant Algorithm’s problem fit the layout and size of the wall perfectly and the different levels of problem-solving were shown. To handle the incredibly high resolution of the video wall, we wrote custom software to run massive video files in parallel.