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Incentivising monitoring in open normative systems

Alechina, Natasha; Halpern, Joseph Y.; Kash, Ian A.; Logan, Brian


Natasha Alechina

Joseph Y. Halpern

Ian A. Kash

Brian Logan


We present an approach to incentivising monitoring for norm violations in open multi-agent systems such as Wikipedia. In such systems, there is no crisp definition of a norm violation; rather, it is a matter of judgement whether an agent’s behaviour conforms to generally accepted standards of behaviour. Agents may legitimately disagree about borderline cases. Using ideas from scrip systems and peer prediction, we show how to design a mechanism that incentivises agents to monitor each other’s behaviour for norm violations. The mechanism keeps the probability of undetected violations (submissions that the majority of the community would consider not conforming to standards) low, and is robust against collusion by the monitoring agents.


Alechina, N., Halpern, J. Y., Kash, I. A., & Logan, B. (2017). Incentivising monitoring in open normative systems.

Conference Name The Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17)
End Date Feb 9, 2017
Acceptance Date Nov 16, 2016
Publication Date Feb 4, 2017
Deposit Date May 10, 2017
Publicly Available Date May 10, 2017
Peer Reviewed Peer Reviewed
Public URL
Publisher URL


Alechina++-17a.pdf (222 Kb)

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