构建行为统一框架，让智能体与对象协同更灵活。
Behavioral Universe Network (BUN): A Behavioral Information-Based Framework for Complex Systems
- 将主体、客体、行为统一为可交互的实体
- 通过信息触发与自适应规则实现多智能体协调
- 适合复杂系统建模与跨域智能应用开发
现代数字生态系统中，自主实体在不同领域间存在复杂的动态交互。传统模型常将智能体与对象分离，缺乏统一基础来捕捉其交互行为。本文提出行为宇宙网络（BUN），基于智能体-交互-行为（AIB）形式化框架，将主体（活跃智能体）、对象（资源）和行为（操作）视为第一类实体，均受共享的行为信息库（BIB）约束。我们阐述了AIB核心概念，并展示BUN如何利用信息驱动的触发机制、语义增强和自适应规则来协调多智能体系统。关键优势包括：提升行为分析能力、强适应性及跨领域互操作性。最后，我们定位BUN为下一代数字治理与智能应用的重要基础。
原文摘要 · Abstract (English)
Modern digital ecosystems feature complex, dynamic interactions among autonomous entities across diverse domains. Traditional models often separate agents and objects, lacking a unified foundation to capture their interactive behaviors. This paper introduces the Behavioral Universe Network (BUN), a theoretical framework grounded in the Agent-Interaction-Behavior (AIB) formalism. BUN treats subjects (active agents), objects (resources), and behaviors (operations) as first-class entities, all governed by a shared Behavioral Information Base (BIB). We detail the AIB core concepts and demonstrate how BUN leverages information-driven triggers, semantic enrichment, and adaptive rules to coordinate multi-agent systems. We highlight key benefits: enhanced behavior analysis, strong adaptability, and cross-domain interoperability. We conclude by positioning BUN as a promising foundation for next-generation digital governance and intelligent applications.
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