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: "stochastic surveillance strategies for spatial quickest detection"
  Abstract: We design persistent surveillance strategies for the quickest detection of anomalies taking place in an environment of interest. From a set of predefined regions in the environment, a team of autonomous vehicles collects noisy observations, which a control center processes. The overall objective is to minimize detection delay while maintaining the false alarm rate below a desired threshold. We present joint (i) anomaly detection algorithms for the control center and (ii) vehicle routing policies. For the control center, we propose parallel cumulative sum (CUSUM) algorithms (one for each region) to detect anomalies from noisy observations. For the vehicles, we propose a stochastic routing policy, in which the regions to be visited are chosen according to a probability vector. We study stationary routing policy (the probability vector is constant) as well as adaptive routing policies (the probability vector varies in time as a function of the likelihood of regional anomalies). In the context of stationary policies, we design a performance metric and minimize it to design an efficient stationary routing policy. Our adaptive policy improves upon the stationary counterpart by adaptively increasing the selection probability of regions with high likelihood of anomaly. Finally, we show the effectiveness of the proposed algorithms through numerical simulations and a persistent surveillance experiment.

Connected through hyperedge HE-1 (induced by source paper "robotic surveillance based on the meeting time of random walks"):
  with members:
    - "convergence time for unbiased quantized consensus over static and dynamic networks"
    - "coalescing random walks and voting on connected graphs"
    - "supervised random walks predicting and recommending links in social networks"

Connected through hyperedge HE-2 (induced by source paper "utility design for distributed resource allocation part ii applications to submodular covering and supermodular problems"):
  with members:
    - "distributed resource allocation through utility design part i optimizing the performance certificates via the price of anarchy"
    - "the impact of local information on the performance of multiagent systems"
    - "competitive caching of contents in 5g edge cloud networks"
    - "optimal approximation for submodular and supermodular optimization with bounded curvature"
    - "efficient minimization of decomposable submodular functions"
    - "combinatorial auctions with decreasing marginal utilities"
    - "pure nash equilibria hard and easy games"

Connected through hyperedge HE-3 (induced by source paper "distributed resource allocation through utility design part ii applications to submodular supermodular and set covering problems"):
  with members:
    - "distributed resource allocation through utility design part i optimizing the performance certificates via the price of anarchy"
    - "multiagent maximum coverage problems the trade off between anarchy and stability"
    - "competitive caching of contents in 5g edge cloud networks"
    - "optimal approximation for submodular and supermodular optimization with bounded curvature"
    - "efficient minimization of decomposable submodular functions"
    - "combinatorial auctions with decreasing marginal utilities"
    - "pure nash equilibria hard and easy games"

Connected through hyperedge HE-4 (induced by source paper "asynchronous and dynamic coverage control scheme for persistent surveillance missions"):
  with members:
    - "discrete partitioning and coverage control for gossiping robots"

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.RO(Robotics)