ColorEcosystem: Powering Personalized, Standardized, and Trustworthy Agentic Service in massive-agent Ecosystem
Fangwen Wu, Zheng Wu, Jihong Wang, Yunku Chen, Ruiguang Pei, Heyuan Huang, Xin Liao, Xingyu Lou, Huarong Deng, Zhihui Fu, Weiwen Liu, Zhuosheng Zhang, Weinan Zhang, Jun Wang

TL;DR
ColorEcosystem introduces a comprehensive framework for scalable, personalized, and trustworthy agentic services in large multi-agent ecosystems, addressing current challenges of impersonality, lack of standardization, and trust issues.
Contribution
It proposes a novel blueprint with three core components—agent carrier, store, and audit—to enhance personalization, standardization, and trustworthiness at scale.
Findings
Implemented part of ColorEcosystem's functionality.
Open-sourced code available at GitHub.
Addresses key challenges in massive-agent ecosystems.
Abstract
With the rapid development of (multimodal) large language model-based agents, the landscape of agentic service management has evolved from single-agent systems to multi-agent systems, and now to massive-agent ecosystems. Current massive-agent ecosystems face growing challenges, including impersonal service experiences, a lack of standardization, and untrustworthy behavior. To address these issues, we propose ColorEcosystem, a novel blueprint designed to enable personalized, standardized, and trustworthy agentic service at scale. Concretely, ColorEcosystem consists of three key components: agent carrier, agent store, and agent audit. The agent carrier provides personalized service experiences by utilizing user-specific data and creating a digital twin, while the agent store serves as a centralized, standardized platform for managing diverse agentic services. The agent audit, based on the…
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Taxonomy
TopicsMulti-Agent Systems and Negotiation · Big Data and Digital Economy · Mobile Agent-Based Network Management
