Language Agent

Language agents are AI systems that leverage large language models (LLMs) to perform complex tasks by interacting with their environment and utilizing external tools. Current research focuses on improving their reasoning abilities, safety, and collaborative capabilities, often employing techniques like reinforcement learning, contrastive learning, and symbolic reasoning within frameworks such as ReAct and others. These advancements are crucial for building reliable and efficient agents for scientific discovery, real-world planning, and other applications where autonomous decision-making and interaction are necessary, addressing limitations in current LLM performance and prompting strategies.