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: "dispersion of mobile robots the power of randomness"
  Abstract: We consider cooperation among insects, modeled as cooperation between mobile robots on a graph. Within this setting, we consider the problem of mobile robot dispersion on graphs. The study of mobile robots on a graph is an interesting paradigm with many interesting problems and applications. The problem of dispersion in this context, introduced by Augustine and Moses Jr. [4], asks that n robots, initially placed arbitrarily on an n node graph, work together to quickly reach a configuration with exactly one robot at each node. Previous work on this problem has looked at the trade-off between the time to achieve dispersion and the amount of memory required by each robot. However, the trade-off was analyzed for deterministic algorithms and the minimum memory required to achieve dispersion was found to be \(\varOmega (\log n)\) bits at each robot. In this paper, we show that by harnessing the power of randomness, one can achieve dispersion with \(O(\log \varDelta )\) bits of memory at each robot, where \(\varDelta \) is the maximum degree of the graph. Further, we show a matching lower bound of \(\varOmega (\log \varDelta )\) bits for any randomized algorithm to solve dispersion. We further extend the problem to a general k-dispersion problem where \(k> n\) robots need to disperse over n nodes such that at most \(\lceil k/n \rceil \) robots are at each node in the final configuration.

Connected through hyperedge HE-1 (induced by source paper "dispersion of mobile robots in the global communication model"):
  with members:
    - "efficient dispersion of mobile robots on graphs"
    - "efficient dispersion of mobile robots on arbitrary graphs and grids"
    - "dispersion of mobile robots a study of memory time trade offs"
    - "a general lower bound for collaborative tree exploration"
    - "time and space optimality of rotor router graph exploration"
    - "algorithms for rapidly dispersing robot swarms in unknown environments"

Connected through hyperedge HE-2 (induced by source paper "efficient dispersion of mobile robots on arbitrary graphs and grids"):
  with members:
    - "efficient dispersion of mobile robots on graphs"
    - "dispersion of mobile robots a study of memory time trade offs"
    - "time and space optimality of rotor router graph exploration"
    - "algorithms for rapidly dispersing robot swarms in unknown environments"

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.DC(Distributed, Parallel, and Cluster Computing)