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Incentive-compatible mechanisms for norm monitoring in open multi-agent systems

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

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Authors

Natasha Alechina

Joseph Y. Halpern

Ian A. Kash

Brian Logan



Abstract

We consider the problem of detecting norm violations in open multi-agent systems (MAS).We show how, using ideas from scrip systems, we can design mechanisms where the agents comprising the MAS are incentivised to monitor the actions of other agents for norm violations. The cost of providing the incentives is not borne by the MAS and does not come from fines charged for norm violations (fines may be impossible to levy in a system where agents are free to leave and rejoin again under a different identity). Instead, monitoring incentives come from (scrip) fees for accessing the services provided by the MAS. In some cases, perfect monitoring (and hence enforcement) can be achieved: no norms will be violated in equilibrium. In other cases, we show that, while it is impossible to achieve perfect enforcement, we can get arbitrarily close; we can make the probability of a norm violation in equilibrium arbitrarily small. We show using simulations that our theoretical results, which apply to systems with a large number of agents, hold for multi-agent systems with as few as 1000 agents—the system rapidly converges to the steady-state distribution of scrip tokens necessary to ensure monitoring and then remains close to the steady state.

Citation

Alechina, N., Halpern, J. Y., Kash, I. A., & Logan, B. (2018). Incentive-compatible mechanisms for norm monitoring in open multi-agent systems. Journal of Artificial Intelligence Research, 62, https://doi.org/10.1613/jair.1.11214

Journal Article Type Article
Acceptance Date Feb 15, 2018
Publication Date Jun 6, 2018
Deposit Date Jun 28, 2018
Publicly Available Date Mar 28, 2024
Journal Journal of Artificial Intelligence Research
Print ISSN 1076-9757
Electronic ISSN 1943-5037
Publisher AI Access Foundation
Peer Reviewed Peer Reviewed
Volume 62
DOI https://doi.org/10.1613/jair.1.11214
Public URL https://nottingham-repository.worktribe.com/output/936756
Publisher URL https://par.nsf.gov/biblio/10059137

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