ColorEcosystem: Powering Personalized, Standardized, and Trustworthy Agentic Service in massive-agent Ecosystem
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arXiv
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| Autori principali: | , , , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866911233685323776 |
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| author | Wu, Fangwen Wu, Zheng Wang, Jihong Chen, Yunku Pei, Ruiguang Huang, Heyuan Liao, Xin Lou, Xingyu Deng, Huarong Fu, Zhihui Liu, Weiwen Zhang, Zhuosheng Zhang, Weinan Wang, Jun |
| author_facet | Wu, Fangwen Wu, Zheng Wang, Jihong Chen, Yunku Pei, Ruiguang Huang, Heyuan Liao, Xin Lou, Xingyu Deng, Huarong Fu, Zhihui Liu, Weiwen Zhang, Zhuosheng Zhang, Weinan Wang, Jun |
| contents | 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 supervision of developer and user activities, ensures the integrity and credibility of both service providers and users. Through the analysis of challenges, transitional forms, and practical considerations, the ColorEcosystem is poised to power personalized, standardized, and trustworthy agentic service across massive-agent ecosystems. Meanwhile, we have also implemented part of ColorEcosystem's functionality, and the relevant code is open-sourced at https://github.com/opas-lab/color-ecosystem. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_21566 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | ColorEcosystem: Powering Personalized, Standardized, and Trustworthy Agentic Service in massive-agent Ecosystem Wu, Fangwen Wu, Zheng Wang, Jihong Chen, Yunku Pei, Ruiguang Huang, Heyuan Liao, Xin Lou, Xingyu Deng, Huarong Fu, Zhihui Liu, Weiwen Zhang, Zhuosheng Zhang, Weinan Wang, Jun Multiagent Systems Computation and Language 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 supervision of developer and user activities, ensures the integrity and credibility of both service providers and users. Through the analysis of challenges, transitional forms, and practical considerations, the ColorEcosystem is poised to power personalized, standardized, and trustworthy agentic service across massive-agent ecosystems. Meanwhile, we have also implemented part of ColorEcosystem's functionality, and the relevant code is open-sourced at https://github.com/opas-lab/color-ecosystem. |
| title | ColorEcosystem: Powering Personalized, Standardized, and Trustworthy Agentic Service in massive-agent Ecosystem |
| topic | Multiagent Systems Computation and Language |
| url | https://arxiv.org/abs/2510.21566 |