Large language models (LLMs) have revolutionized a wide range of domains. In particular, LLMs have been developed as agents to interact with the world and handle various tasks. With the continuous advancement of LLM techniques, LLM agents are set to be the upcoming breakthrough in AI, and they are going to transform the future of our daily life with the support of intelligent task automation and personalization. In this course, we will first discuss fundamental concepts that are essential for LLM agents, including the foundation of LLMs, essential LLM abilities required for task automation, as well as infrastructures for agent development. We will also cover representative agent applications, including code generation, robotics, web automation, medical applications, and scientific discovery. Meanwhile, we will discuss limitations and potential risks of current LLM agents, and share insights into directions for further improvement. Specifically, this course will include the following topics:Foundation of LLMs
Reasoning
Planning, tool use
LLM agent infrastructure
Retrieval-augmented generation
Code generation, data science
Multimodal agents, robotics
Evaluation and benchmarking on agent applications
Privacy, safety and ethics
Human-agent interaction, personalization, alignment
Multi-agent collaboration