Using Incentive Mechanisms for an Adaptive Regulation of Open Multi-Agent Systems
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 139-144.
Abstract
In this paper we propose a mechanism that encourages agents, participating in an open MAS, to follow a desirable behaviour, by introducing modifications in the environment. This mechanism is deployed by using an infrastructure based on institutional agents called incentivators. Each external agent is assigned to an incentivator that is able to discover its preferences, and to learn the suitable modifications in the environment, in order to improve the global utility of a system in response to inadequate design or changes in the population of participating agents. The mechanism is evaluated in a p2p scenario.
@inproceedings{ijcai2011p35,
title = {Using Incentive Mechanisms for an Adaptive Regulation of Open Multi-Agent Systems},
author = {Centeno, Roberto and Billhardt, Holger},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {139--144},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-035},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-035},
}
TY - CPAPER TI - Using Incentive Mechanisms for an Adaptive Regulation of Open Multi-Agent Systems AU - Centeno, Roberto AU - Billhardt, Holger T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 139 EP - 144 DO - 10.5591/978-1-57735-516-8/IJCAI11-035 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-035 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: