Modern digital ecosystems are characterized by complex, dynamic interactions among autonomous entities across diverse domains. Traditional paradigms often treat agents and objects separately, failing to provide a unified theoretical 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 citizens, all governed by a shared Behavioral Information Base (BIB). We first detail the AIB core principles, defining how subjects, objects, and behaviors are formally described and regulated. We then describe BUN as a framework, showcasing how information-driven triggers, semantic object enrichment, and adaptive rules enable highly coordinated multi-agent systems. We highlight the framework's key advantages: more accurate behavior analysis, strong adaptability to dynamic environments, and cross-domain synergies. Finally, we outline open challenges and future work, positioning BUN as a promising foundation for next-generation digital governance and intelligent applications.