Probabilistically Survivable MASs
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 789-794.
Abstract
Multiageht systems (MAS) can "go down" for a large number of reasons, ranging from system malfunctions and power failures to malicious attacks. The placement of agents on nodes is called a deployment of the MAS. We develop a probabilistic model of survivability of a deployed MAS and provide two algorithms to compute the probability of survival of a deployed MAS. Our probabilistic model does not make independence assumptions though ·such assumptions can be added if so desired. An optimal deployment of a MAS is one that mu:imizes its survival probability. We provide a mathematical answerto this question. an algorithm that computes an exact solution to this problem, as well as several algorithms that quickly compute approximate solutions to the problem. We have implemented our algorithms - our implementation demonstrates that computing deployments can be done scalably.
@inproceedings{ijcai2003p114,
title = {Probabilistically Survivable MASs},
author = {Kraus, Sarit and Subrahmanian, V. S. and Tas, Nazif Cihan},
booktitle = {Proceedings of the Eighteenth International Joint Conference on
Artificial Intelligence, {IJCAI-03}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Georg Gottlob},
pages = {789--794},
year = {2003},
url = {https://ijcai.org/proceedings/2003/114},
}
TY - CPAPER TI - Probabilistically Survivable MASs AU - Kraus, Sarit AU - Subrahmanian, V. S. AU - Tas, Nazif Cihan T2 - Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03 PB - International Joint Conferences on Artificial Intelligence PY - 2003 SP - 789 EP - 794 UR - https://ijcai.org/proceedings/2003/114 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: