LLM Driven Agent

LLM-driven agents represent a burgeoning field exploring the use of large language models to create autonomous agents capable of complex tasks and interactions. Current research focuses on developing multi-agent systems, often employing iterative processes combining static and dynamic analysis to improve agent performance and safety, and evaluating agent capabilities through novel metrics focusing on information exchange and expressiveness. These agents are being applied across diverse domains, including software engineering, legal proceedings, healthcare, and autonomous driving, demonstrating the potential for LLMs to model and solve real-world problems through collaborative, knowledge-driven approaches. The resulting advancements contribute to both a deeper understanding of LLM capabilities and the development of more robust and adaptable AI systems.