An upcoming project exploring multi-agent control and consensus protocols, likely incorporating reinforcement learning for decentralized coordination. This page will be updated as the project scope and approach are finalized.
This project will build on concepts from the Multi-Agent Systems course at Berkeley, exploring how groups of autonomous agents can coordinate their behavior without centralized control. Potential directions include consensus-based formation control, cooperative task allocation, or multi-agent reinforcement learning for collective decision-making.
Details on the specific problem formulation, approach, and results will be added as the project develops.
🚧 This project is currently being scoped. Check back soon for updates.