As part of my undergraduate studies, I developed a multi-agent system in the Unity game engine to explore the principles of collaborative problem-solving. The project involved creating a simulation in which multiple “smart agents,” represented as lumberjacks, had to work together to cut down all the trees in a given area.
The agents were programmed to use a variety of pathfinding algorithms, including Djikstra and A*, as well as random movements, to navigate the environment and avoid obstacles.
The key feature of the system was the agents’ ability to learn from their environment and share that information with each other. This allowed them to collectively build a map of the area and determine the most efficient way to complete the task. This project was a great introduction to the principles of artificial intelligence and multi-agent systems, and it gave me a solid foundation for my later work in this area.
