Mapping Human Anti-collusion Mechanisms to Multi-agent AI

February 09, 2026

Reading time: 1 minute

...

📝 Original Info

Title: Mapping Human Anti-collusion Mechanisms to Multi-agent AI
ArXiv ID: 2601.00360
Date: 2026-01-01
Authors: Jamiu Adekunle Idowu, Ahmed Almasoud, Ayman Alfahid

📝 Abstract

As multi-agent AI systems become increasingly autonomous, evidence shows they can develop collusive strategies similar to those long observed in human markets and institutions. While human domains have accumulated centuries of anti-collusion mechanisms, it remains unclear how these can be adapted to AI settings. This paper addresses that gap by (i) developing a taxonomy of human anticollusion mechanisms, including sanctions, leniency & whistleblowing, monitoring & auditing, market design, and governance and (ii) mapping them to potential interventions for multi-agent AI systems. For each mechanism, we propose implementation approaches. We also highlight open challenges, such as the attribution problem (difficulty attributing emergent coordination to specific agents) identity fluidity (agents being easily forked or modified) the boundary problem (distinguishing beneficial cooperation from harmful collusion) and adversarial adaptation (agents learning to evade detection).

📄 Full Content

...(본문 내용이 길어 생략되었습니다. 사이트에서 전문을 확인해 주세요.)

Mapping Human Anti-collusion Mechanisms to Multi-agent AI

📝 Original Info

📝 Abstract

📄 Full Content

Table of Contents

Table of Contents

📝 Original Info

📝 Abstract

📄 Full Content

Start searching

No results found