human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "a quadratic lower bound for the convergence rate in the one dimensional hegselmann krause bounded confidence dynamics"
  Abstract: Let f_{k}(n) be the maximum number of time steps taken to reach equilibrium by a system of n agents obeying the k-dimensional Hegselmann-Krause bounded confidence dynamics. Previously, it was known that \Omega(n) = f_{1}(n) = O(n^3). Here we show that f_{1}(n) = \Omega(n^2), which matches the best-known lower bound in all dimensions k >= 2.

Connected through hyperedge HE-1 (induced by source paper "a tutorial on modeling and analysis of dynamic social networks part i"):
  with members:
    - "on the analysis of the degroot friedkin model with dynamic relative interaction matrices"
    - "opinion evolution in time varying social influence networks with prejudiced agents"
    - "differential inequalities in multi agent coordination and opinion dynamics modeling"
    - "distributed algorithms for computation of centrality measures in complex networks"
    - "novel multidimensional models of opinion dynamics in social networks"
    - "open multi agent systems gossiping with random arrivals and departures"
    - "active sensing of social networks"
    - "structural balance and opinion separation in trust mistrust social networks"

Connected through hyperedge HE-2 (induced by source paper "how friends and non determinism affect opinion dynamics"):
  with members:
    - "inertial hegselmann krause systems"
    - "an improved energy argument for the hegselmann krause model"
    - "on the convergence of the hegselmann krause system"

Connected through hyperedge HE-3 (induced by source paper "an improved energy argument for the hegselmann krause model"):
  with members:
    - "game theoretic analysis of the hegselmann krause model for opinion dynamics in finite dimensions"
    - "on the convergence of the hegselmann krause system"

Question: Please tell me which class the center node 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)