ColorEcosystem: Powering Personalized, Standardized, and Trustworthy Agentic Service in massive-agent Ecosystem

2025-10-24

AI Summary

To address three critical challenges in large-scale multi-agent ecosystems—insufficient service personalization, lack of standardization, and unverifiable agent behavior—this paper proposes a tripartite collaborative architecture. First, agent carriers enable dynamic digital twin modeling for fine-grained personalized service provisioning. Second, a centralized agent marketplace provides unified service registration, discovery, and version management to enforce standardization. Third, a lightweight behavior-log-based auditing mechanism ensures behavioral trustworthiness. The system integrates multimodal large language models, digital twin technology, service registry infrastructure, and behavioral monitoring to establish an end-to-end verifiable service governance framework. A fully open-source prototype demonstrates significant improvements: +23.6% in service matching accuracy, −41.2% reduction in interface heterogeneity overhead, and >99.8% malicious behavior detection rate.

Technology Category

• Multiagent Systems: Adversarial Agents
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Machine-in-the-loop, human agency and autonomy

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 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.

Problem

• Addressing impersonal service experiences in massive-agent ecosystems
• Establishing standardized platforms for managing diverse agentic services
• Ensuring trustworthy behavior through audit mechanisms for integrity

Innovation

• Agent carrier enables personalized service via digital twin
• Agent store standardizes management of diverse agent services
• Agent audit ensures integrity through activity supervision