A Privacy Preserving Algorithm for Multi-Agent Planning and Search
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 1530-1535.
Abstract
To engage diverse agents in cooperative behavior, it is important, even necessary, to provide algorithms that do not reveal information that is private or proprietary.A number of recent planning algorithms enable agents to plan together for shared goals without disclosing information about their private state and actions. But these algorithms lack clear and formal privacy guarantees: the fact that they do not require agents to explicitly reveal private information, does not imply that such information cannot be deduced. The main contribution of this paper is an enhanced version of the distributed forward-search planning framework of Nissim and Brafman that reveals less information than the original algorithm, and the first, to our knowledge, discussion and formal proof of privacy guarantees for distributed planning and search algorithms.
@inproceedings{ijcai2015p219,
title = {A Privacy Preserving Algorithm for Multi-Agent Planning and Search},
author = {Brafman, Ronen I.},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {1530--1535},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/219},
}
TY - CPAPER TI - A Privacy Preserving Algorithm for Multi-Agent Planning and Search AU - Brafman, Ronen I. T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 1530 EP - 1535 UR - https://ijcai.org/proceedings/2015/219 ER -Copied
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