Generalist Agent
Generalist agents are artificial intelligence systems designed to perform a wide range of tasks and adapt to diverse environments, unlike specialized agents trained for single purposes. Current research focuses on developing robust model architectures, often incorporating large language models (LLMs) and reinforcement learning (RL), to improve generalization across tasks and modalities, including robotic manipulation, web browsing, and spreadsheet manipulation. These advancements are significant because they move AI closer to truly general-purpose intelligence, with potential applications spanning various fields from software development to personalized education and robotics.
Papers
OS-ATLAS: A Foundation Action Model for Generalist GUI Agents
Zhiyong Wu, Zhenyu Wu, Fangzhi Xu, Yian Wang, Qiushi Sun, Chengyou Jia, Kanzhi Cheng, Zichen Ding, Liheng Chen, Paul Pu Liang, Yu Qiao
Kinetix: Investigating the Training of General Agents through Open-Ended Physics-Based Control Tasks
Michael Matthews, Michael Beukman, Chris Lu, Jakob Foerster