Foraging with Swarm Robotics
Balancing information and expected rewards during swarm foraging
In this project, I explored how robotic agents operating in a swarm must balance known rewards with the value of current information while performing foraging. The algorithm controls agent behavior during foraging and task completion, aiming to maximize rewards gathered while ensuring agents have up-to-date information about their environment and potential rewards. I then compared performance with the algorithm to a series of balance approaches using a custom ARGoS simulation. Check out the technical details in the report below!
