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In this paper, a generalized convex network optimization problem with local domains and constraints is formulated and solved by using distributed multi-agent dynamics. Within the framework of the present network optimization, it is assumed that the local system states and constraints are available to an individual agent and each agent may only share information with its neighbors. A distributed PI-based...
We examine the interplay between learning and privacy over multiagent consensus networks. The learning objective of each individual agent consists of computing some global network statistic, and is accomplished by means of a consensus protocol. The privacy objective consists of preventing inference of the individual agents’ data from the information exchanged during the consensus stages, and is accomplished...
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