Ziya Gokalp​​​​​​​

Machine-to-Machine Intelligence (M2MINT™) is a conceptual framework for understanding how autonomous AI agents may gather intelligence about other AI systems. Framework examines how an agent could observe, test, profile, model, predict and adapt to another system’s behaviour, capabilities and decision patterns.

 

The framework distinguishes this broader intelligence process from machine espionage, in which an agent seeks information about another system without its operator’s authorization. It also considers machine counterintelligence: how a targeted system might detect, attribute and respond to such activity.

 

M2MINT™ is a framework for research, not a claim that these activities have been demonstrated as a mature field. It raises questions about security, attribution and human oversight as AI agents become more autonomous.

Framework developed by Ziya Gökalp · September 2026