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: "on distributed cooperative decision making in multiarmed bandits"
  Abstract: We study the explore-exploit tradeoff in distributed cooperative decision-making using the context of the multiarmed bandit (MAB) problem. For the distributed cooperative MAB problem, we design the cooperative UCB algorithm that comprises two interleaved distributed processes: (i) running consensus algorithms for estimation of rewards, and (ii) upper-confidence-bound-based heuristics for selection of arms. We rigorously analyze the performance of the cooperative UCB algorithm and characterize the influence of communication graph structure on the decision-making performance of the group.

Connected through hyperedge HE-1 (induced by source paper "a decentralized communication policy for multi agent multi armed bandit problems"):
  with members:
    - "decentralized cooperative stochastic multi armed bandits"
    - "distributed cooperative decision making in multiarmed bandits frequentist and bayesian algorithms"
    - "collaborative learning of stochastic bandits over a social network"

Connected through hyperedge HE-2 (induced by source paper "collaborative learning with limited interaction tight bounds for distributed exploration in multi armed bandits"):
  with members:
    - "improved algorithms for collaborative pac learning"
    - "tight bounds for collaborative pac learning via multiplicative weights"
    - "adaptive multiple arm identification"
    - "towards instance optimal bounds for best arm identification"
    - "delay and cooperation in nonstochastic bandits"
    - "multi player bandits a musical chairs approach"
    - "distributed exploration in multi armed bandits"
    - "multiple identifications in multi armed bandits"

Connected through hyperedge HE-3 (induced by source paper "individual regret in cooperative nonstochastic multi armed bandits"):
  with members:
    - "multi player bandits the adversarial case"
    - "cooperative online learning keeping your neighbors updated"
    - "distributed cooperative decision making in multiarmed bandits frequentist and bayesian algorithms"
    - "collaborative learning of stochastic bandits over a social network"
    - "delay and cooperation in nonstochastic bandits"
    - "multi player bandits a musical chairs approach"
    - "concurrent bandits and cognitive radio networks"
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"

Connected through hyperedge HE-4 (induced by source paper "decentralized cooperative stochastic bandits"):
  with members:
    - "distributed cooperative decision making in multiarmed bandits frequentist and bayesian algorithms"
    - "distributed clustering of linear bandits in peer to peer networks"
    - "delay and cooperation in nonstochastic bandits"
    - "distributed exploration in multi armed bandits"
    - "online learning under delayed feedback"
    - "regret analysis of stochastic and nonstochastic multi armed bandit problems"
    - "distributed algorithms for learning and cognitive medium access with logarithmic regret"
    - "gossip algorithms for distributed signal processing"

Connected through hyperedge HE-5 (induced by source paper "cooperation speeds surfing use co bandit"):
  with members:
    - "congestion aware distributed network selection for integrated cellular and wi fi networks"
    - "delay and cooperation in nonstochastic bandits"
    - "efficient optimal learning for contextual bandits"
    - "performance and convergence of multi user online learning"

Connected through hyperedge HE-6 (induced by source paper "an option and agent selection policy with logarithmic regret for multi agent multi armed bandit problems on random graphs"):
  with members:
    - "distributed cooperative decision making in multiarmed bandits frequentist and bayesian algorithms"

Connected through hyperedge HE-7 (induced by source paper "decentralized exploration in multi armed bandits"):
  with members:
    - "corrupt bandits for preserving local privacy"
    - "best arm identification in linear bandits"
    - "concurrent bandits and cognitive radio networks"
    - "distributed exploration in multi armed bandits"
    - "calibrating data to sensitivity in private data analysis"
    - "distributed non stochastic experts"
    - "composition attacks and auxiliary information in data privacy"

Connected through hyperedge HE-8 (induced by source paper "decentralized cooperative stochastic multi armed bandits"):
  with members:
    - "distributed cooperative decision making in multiarmed bandits frequentist and bayesian algorithms"
    - "delay and cooperation in nonstochastic bandits"
    - "distributed exploration in multi armed bandits"
    - "gossip algorithms for distributed signal processing"

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)