The Dynamic Verifiable Multi-Agent Human Agentic Loyalty Loop (DVM-HALL) Model and the Net Human-Agent Score (NHAS) in Autonomous Commerce

arXiv cs.AI · 18 hours ago

Researchers introduced the Dynamic Verifiable Multi-Agent Human Agentic Loyalty Loop model to explain how autonomous AI agents make purchasing decisions and maintain brand loyalty, addressing limitations in traditional consumer loyalty frameworks. The model incorporates a softmax probability formulation combining human emotional equity, agent utility, calibrated trust, and execution factors like gas costs and slippage in DeFi contexts. The Net Human-Agent Score metric measures human-agent alignment through feedback logs and verifiable receipts to help brands adapt as AI agents become active market participants.