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Distributed decision-making algorithms with multiple manipulative actors

Abstract:

Distributed decision-making in the presence of multiple manipulative actors is studied, in the context of a linear distributed-consensus algorithm which has been enhanced to represent feedback controls enacted by the actors. The main contribution of the work is to evaluate the interplay among the manipulative actors in deciding: (1) the asymptotic decisions reached by the agents and (2) network's transient dynamics. In particular, the dependence of the asymptotic opinions on the network's topology and the manipulative actors’ control schemes is characterized. Then, the impacts of the actors’ control schemes on the intrinsic settling dynamics of the network, as well on each others’ transfer functions, is studied. The analyses show that the asymptotics and transients both show a complex spatial dependence on the relative locations of manipulated agents within the network. Two examples are used to illustrate the results.