User Behavior Simulation with Large Language Model based Agents

Understand

Simulating high quality user behavior data has always been a fundamental problem in human-centered applications, where the major difficulty originates from the intricate mechanism of human decision process.

• Recently, substantial evidences have suggested that by learning huge amounts of web knowledge, large language models (LLMs) can achieve human-like intelligence.
• We believe these models can provide significant opportunities to more believable user behavior simulation.
• To inspire such direction, we propose an LLM-based agent framework and design a sandbox environment to simulate real user behaviors.