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 framework for automated competitive analysis of on line scheduling of firm deadline tasks"
  Abstract: We present a flexible framework for the automated competitive analysis of on-line scheduling algorithms for firm-deadline real-time tasks based on multi-objective graphs: Given a taskset and an on-line scheduling algorithm specified as a labeled transition system, along with some optional safety, liveness, and/or limit-average constraints for the adversary, we automatically compute the competitive ratio of the algorithm w.r.t. a clairvoyant scheduler. We demonstrate the flexibility and power of our approach by comparing the competitive ratio of several on-line algorithms, including $D^{over}$, that have been proposed in the past, for various tasksets. Our experimental results reveal that none of these algorithms is universally optimal, in the sense that there are tasksets where other schedulers provide better performance. Our framework is hence a very useful design tool for selecting optimal algorithms for a given application.

Connected through hyperedge HE-1 (induced by source paper "perfect information stochastic games with generalized mean payoff objectives"):
  with members:
    - "unifying two views on multiple mean payoff objectives in markov decision processes"
    - "multidimensional beyond worst case and almost sure problems for mean payoff objectives"
    - "fixed dimensional energy games are in pseudo polynomial time"
    - "two player perfect information shift invariant submixing stochastic games are half positional"
    - "markov decision processes with multiple long run averageobjectives"
    - "synthesis from ltl specifications with mean payoff objectives"
    - "the complexity of multi mean payoff and multi energy games"
    - "finite memory strategy synthesis for robust multidimensional mean payoff objectives"

Connected through hyperedge HE-2 (induced by source paper "the complexity of multi mean payoff and multi energy games"):
  with members:
    - "polynomial time algorithms for energy games with special weight structures"
    - "looking at mean payoff and total payoff through windows"
    - "efficient controller synthesis for consumption games with multiple resource types"
    - "strategy synthesis for multi dimensional quantitative objectives"
    - "hyperplane separation technique for multidimensional mean payoff games"
    - "reachability games on extended vector addition systems with states"
    - "mean payoff automaton expressions"

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.DS(Data Structures and Algorithms)