Bumping strategies for the multiagent agreement problem
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Impact of problem centralization in distributed constraint optimization algorithms
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Autonomous Agents and Multi-Agent Systems
Nogood based asynchronous distributed optimization (ADOPT ng)
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Multiply-constrained distributed constraint optimization
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
A genetic algorithm for privacy preserving combinatorial optimization
Proceedings of the 9th annual conference on Genetic and evolutionary computation
SSDPOP: improving the privacy of DCOP with secret sharing
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Privacy-preserving linear programming
Proceedings of the 2009 ACM symposium on Applied Computing
An overview of privacy improvements to k-optimal DCOP algorithms
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Privatizing constraint optimization
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Longest common subsequence as private search
Proceedings of the 8th ACM workshop on Privacy in the electronic society
Quantifying privacy in multiagent planning
Multiagent and Grid Systems - Planning in multiagent systems
Multi-party indirect indexing and applications
ASIACRYPT'07 Proceedings of the Advances in Crypotology 13th international conference on Theory and application of cryptology and information security
Balancing local resources and global goals in multiply-constrained DCOP
Multiagent and Grid Systems
Privacy-preserving activity scheduling on mobile devices
Proceedings of the first ACM conference on Data and application security and privacy
Efficient distributed linear programming with limited disclosure
DBSec'11 Proceedings of the 25th annual IFIP WG 11.3 conference on Data and applications security and privacy
Meetings through the cloud: Privacy-preserving scheduling on mobile devices
Journal of Systems and Software
Coordinating logistics operations with privacy guarantees
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Protecting privacy through distributed computation in multi-agent decision making
Journal of Artificial Intelligence Research
Secure and efficient distributed linear programming
Journal of Computer Security - DBSec 2011
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Several naturally distributed negotiation/cooperation problems with privacy requirements can be modeled within the distributed constraint satisfaction framework, where the constraints are secrets of the participants. Most of the existing techniques aim at various tradeoffs between complexity and privacy guarantees, while others aim to maximize privacy first [12, 7, 3, 4, 11]. In [7] we introduced a first technique allowing agents to solve distributed constraint problems (DisCSPs), without revealing anything and without trusting each other or some server. The technique we propose now is a dm times improvement for m variables of domain size d. On the negative side, the fastest versions of the new technique require storing of O(d{m}) big integers. From a practical point of view, we improve the privacy with which these problems can be solved, and improve the efficiency with which[n-1/2]-privacy can be achieved, while it remains inapplicable for larger problems. The technique of [7] has a simple extension to optimization for distributed weighted CSPs. However, that obvious extension leaks to everybody sensitive information concerning the quality of the computed solution.We found a way to avoid this leak, which constitutes another contribution of this paper.