AgentStore: Scalable Integration of Heterogeneous Agents As Specialized
  Generalist Computer Assistant
Authors: name: Chengyou Jia, name: Minnan Luo, name: Zhuohang Dang, name: Qiushi Sun, name: Fangzhi Xu, name: Junlin Hu, name: Tianbao Xie, name: Zhiyong Wu

Digital agents capable of automating complex computer tasks have attracted
considerable attention due to their immense potential to enhance human-computer
interaction. However, existing agent methods exhibit deficiencies in their
generalization and specialization capabilities, especially in handling
open-ended computer tasks in real-world environments. Inspired by the rich
functionality of the App store, we present AgentStore, a scalable platform
designed to dynamically integrate heterogeneous agents for automating computer
tasks. AgentStore empowers users to integrate third-party agents, allowing the
system to continuously enrich its capabilities and adapt to rapidly evolving
operating systems. Additionally, we propose a novel core MetaAgent
with the AgentToken strategy to efficiently manage diverse agents and
utilize their specialized and generalist abilities for both domain-specific and
system-wide tasks. Extensive experiments on three challenging benchmarks
demonstrate that AgentStore surpasses the limitations of previous systems with
narrow capabilities, particularly achieving a significant improvement from
11.21\% to 23.85\% on the OSWorld benchmark, more than doubling the previous
results. Comprehensive quantitative and qualitative results further demonstrate
AgentStore's ability to enhance agent systems in both generalization and
specialization, underscoring its potential for developing the specialized
generalist computer assistant. All our codes will be made publicly available in
https://chengyou-jia.github.io/AgentStore-Home.