Incentivising monitoring in open normative systems

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 behavi...

Full description

Bibliographic Details
Main Authors: Alechina, Natasha, Halpern, Joseph Y., Kash, Ian A., Logan, Brian
Format: Conference or Workshop Item
Published: 2017
Online Access:https://eprints.nottingham.ac.uk/42719/
_version_ 1848796552421703680
author Alechina, Natasha
Halpern, Joseph Y.
Kash, Ian A.
Logan, Brian
author_facet Alechina, Natasha
Halpern, Joseph Y.
Kash, Ian A.
Logan, Brian
author_sort Alechina, Natasha
building Nottingham Research Data Repository
collection Online Access
description 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.
first_indexed 2025-11-14T19:49:48Z
format Conference or Workshop Item
id nottingham-42719
institution University of Nottingham Malaysia Campus
institution_category Local University
last_indexed 2025-11-14T19:49:48Z
publishDate 2017
recordtype eprints
repository_type Digital Repository
spelling nottingham-427192020-05-04T18:35:59Z https://eprints.nottingham.ac.uk/42719/ Incentivising monitoring in open normative systems Alechina, Natasha Halpern, Joseph Y. Kash, Ian A. Logan, Brian 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. 2017-02-04 Conference or Workshop Item PeerReviewed Alechina, Natasha, Halpern, Joseph Y., Kash, Ian A. and Logan, Brian (2017) Incentivising monitoring in open normative systems. In: The Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), 4-9 February, 2017, San Francisco, California, USA.. http://www.aaai.org/ocs/index.php/AAAI/AAAI17/paper/download/14911/13776
spellingShingle Alechina, Natasha
Halpern, Joseph Y.
Kash, Ian A.
Logan, Brian
Incentivising monitoring in open normative systems
title Incentivising monitoring in open normative systems
title_full Incentivising monitoring in open normative systems
title_fullStr Incentivising monitoring in open normative systems
title_full_unstemmed Incentivising monitoring in open normative systems
title_short Incentivising monitoring in open normative systems
title_sort incentivising monitoring in open normative systems
url https://eprints.nottingham.ac.uk/42719/
https://eprints.nottingham.ac.uk/42719/