- Robotics, Swarm Robotics
- Collective Intelligence, Artificial Intelligence
- Evolutionary Computation, RL algorithms
Explore the field of Swarm Robotics 🐜🐝🤖.
Swarm robotics is a field that combines principles of collective robotics and swarm intelligence. It is based on the idea that a group of simple robots, operating on local rules, can achieve complex behaviors at a global level without individual members having a complete global view. However, current research in swarm robotics is limited by certain drawbacks, such as the need to maintain a narrow range of optimal parameters in self-organizing systems, and the difficulty of designing micro-level controllers that produce desired global behaviors.
To address these challenges, I am interested in using evolutionary and machine learning approaches, such as evolutionary computation, reinforcement learning and imitation learning, to improve our understanding of collective behaviors in artificial collectives. I believe that these approaches can help regulate the behavior of system components within desirable ranges, estimate the parameters that regulate natural swarms, and identify the micro-level rules and controllers needed to achieve desired macroscopic behaviors.
My overall goal is to explore the potential of evolutionary swarm robotics and machine learning to build artificial collectives with the same scale and complexity as those found in nature. I am also hope to inspire others to pursue research in this field.