Adaptation of Organizational Models for Multi-Agent Systems Based on Max Flow Networks
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 1321-1325.
Abstract
Organizational models within multi-agent systems literature are of a static nature. Depending upon circumstances adaptation of the organizational model can be essential to ensure a continuous successful function of the system. This paper presents an approach based on max flow networks to dynamically adapt organizational models to environmental fluctuation. First, a formal mapping between a well-known organizational modeling framework and max flow networks is presented. Having such a mapping maintains the insightful structure of an organizational model whereas specifying efficient adaptation algorithms based on max flow networks can be done as well. Thereafter two adaptation mechanisms based on max flow networks are introduced each being appropriate for different environmental characteristics.
@inproceedings{ijcai2007p213,
title = {Adaptation of Organizational Models for Multi-Agent Systems Based on Max Flow Networks},
author = {Hoogendoorn, Mark},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {1321--1325},
year = {2007},
url = {https://ijcai.org/proceedings/2007/213},
}
TY - CPAPER TI - Adaptation of Organizational Models for Multi-Agent Systems Based on Max Flow Networks AU - Hoogendoorn, Mark T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 1321 EP - 1325 UR - https://ijcai.org/proceedings/2007/213 ER -Copied
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