This research uses evolutionary game theory to model interactions between LLM agents, developers, and regulators to understand trust dynamics in AI ecosystems.

• LLMs embedded as agents in game-theoretic frameworks reveal strategic behaviors under different regulatory conditions
• The study quantitatively analyzes trust dilemmas between AI stakeholders, including developers, regulators, and users
• Results provide insights into how different regulatory approaches influence cooperation and trustworthiness in AI development
• Findings suggest data-driven approaches for designing effective AI governance frameworks

For security professionals, this research offers valuable insights into designing regulatory environments that promote trustworthy AI systems while balancing innovation and safety concerns.

Do LLMs trust AI regulation? Emerging behaviour of game-theoretic LLM agents