Multi Agent Communication

Multi-agent communication research focuses on enabling effective information exchange between multiple artificial agents to enhance collaboration and achieve shared goals. Current research emphasizes efficient communication protocols, often employing techniques like graph neural networks and attention mechanisms to manage communication overhead and improve the interpretability of agent "languages," while also addressing challenges like adversarial attacks and bandwidth limitations. This field is crucial for advancing artificial intelligence, particularly in areas like robotics, autonomous systems, and financial markets, where coordinated multi-agent behavior is essential for complex task completion.