Agent4Rec

Agent4Rec is an innovative recommender system simulator that features 1,000 LLM-powered generative agents. This advanced platform simulates realistic user interactions in the context of movie recommendations, allowing for in-depth analysis and understanding of human behavior within recommendation environments. By leveraging the capabilities of large language models, Agent4Rec provides valuable insights into how users engage with recommendation systems. This simulation not only enhances the understanding of user preferences and decision-making processes but also aids in refining the algorithms that drive effective recommendations. With its focus on realistic interactions, Agent4Rec serves as a powerful tool for researchers and developers looking to improve the effectiveness of recommendation systems in various applications.

Coding • Closed Source