Multi Agent Collaboration

Multi-agent collaboration (MAC) research focuses on designing and optimizing systems where multiple AI agents work together to achieve complex goals, surpassing the capabilities of individual agents. Current research emphasizes leveraging large language models (LLMs) within various agent architectures, often incorporating hierarchical structures, decentralized learning, and mechanisms for efficient communication and conflict resolution to improve task completion and reasoning accuracy. This field is significant for advancing AI safety, improving decision-making in diverse domains (healthcare, law, engineering), and enabling more sophisticated and robust AI systems for practical applications.