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Behavioral Universe Network (BUN): A Behavioral Information-Based Framework for Complex Systems

arXiv 2504.15146 ↗First posted 21 Apr 2025cs.AIcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 2 of its 29 references that are in the map. First posted on arXiv 21 Apr 2025.

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2 of 29 references.

References · 2

  1. 2018Multi-Agent Common Knowledge Reinforcement Learningcited by 31
  2. 2024Computational Diplomacy: How "hackathons for good" feed a participatory future for multilateralism in the digital agecited by 1

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