human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "nash equilibrium seeking in subnetwork zero sum games with switching communication graphs"):
  Abstract: In this paper, we investigate a distributed Nash equilibrium seeking problem for a time-varying multi-agent network consisting of two subnetworks. We propose a subgradient-based distributed algorithm to seek a Nash equilibrium of a zero-sum game, where the two subnetworks share the same sum objective function. We show that the proposed distributed algorithm with homogenous stepsize can achieve a Nash equilibrium under uniformly jointly strongly connected (UJSC) weight-balanced digraphs. Then for weight-unbalanced graphs, we show, by considering a special case, that generally a Nash equilibrium cannot be achieved with homogenous stepsize unless certain conditions on the objective functions hold. Next we show that for any UJSC digraphs, there always exist stepsizes under which a Nash equilibrium can be achieved. Finally, for two general weight-unbalanced cases, we show that by adaptively updating the stepsize along with the arc weights in the proposed algorithm, a convergence to the Nash equilibrium can still be guaranteed.

Includes members:
  Member "randomized optimal consensus of multi agent systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "network flows that solve linear equations")
  Member "reaching an optimal consensus dynamical systems that compute intersections of convex sets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a tutorial on modeling and analysis of dynamic social networks part i")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.SY(Systems and Control)