Multi-Agent Coordination

Collaborative Intelligence Through Agent Networks

Research Overview

Multi-agent systems represent the future of scalable AI, where multiple specialized agents collaborate to solve problems beyond individual capabilities. Our research addresses coordination, communication protocols, and emergent behaviors in agent societies.

Key Focus Areas

Distributed Decision-Making

Consensus mechanisms for agent collectives

Agent Communication Protocols

Efficient information exchange between autonomous agents

Coalition Formation

Dynamic team assembly based on task requirements

Competitive and Cooperative Dynamics

Game-theoretic approaches to multi-agent scenarios

Swarm Intelligence

Emergent problem-solving from simple agent interactions

Active Projects

CollaborateAI: Framework for training cooperative agent teams
Agent Marketplace: Platform for specialized agents to negotiate and collaborate
Distributed RL at Scale: Training frameworks for 100+ agent scenarios