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In this paper, we discuss the distributed design for binary classification based on the nonlinear support vector machine in a time-varying multi-agent network when the training data sets are distributedly located and unavailable to all agents. In particular, the aim is to find a global large margin classifier and then enable each agent to classify any new input data into one of the two labels in the binary classification without sharing its all local data with other agents. We formulate the support...
This paper studies a new model of social opinion dynamics in multiagent system by counting in two important factors, individual susceptibility and anchoring effect. Different from many existing models only focusing on one factor, this model can exhibit not only agreement phenomena, but also disagreement phenomena such as clustering and fluctuation, during opinion evolution. Then we provide several conditions to show how individual susceptibility and anchoring effect work on steady-state behaviors...
In this paper, we consider a distributed Bayesian Nash equilibrium (BNE) seeking problem in incomplete-information aggregative games, which is a generalization of either Bayesian games or deterministic aggregative games. We handle the aggregation function to adapt to incomplete-information situations. Since the feasible strategies are infinite-dimensional functions and lie in a non-compact set, the continuity of types brings barriers to seeking equilibria. To this end, we discretize the continuous...
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