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: "looking at mean payoff through foggy windows"
  Abstract: Mean-payoff games (MPGs) are infinite duration two-player zero-sum games played on weighted graphs. Under the hypothesis of perfect information, they admit memoryless optimal strategies for both players and can be solved in NP-intersect-coNP. MPGs are suitable quantitative models for open reactive systems. However, in this context the assumption of perfect information is not always realistic. For the partial-observation case, the problem that asks if the first player has an observation-based winning strategy that enforces a given threshold on the mean-payoff, is undecidable. In this paper, we study the window mean-payoff objectives that were introduced recently as an alternative to the classical mean-payoff objectives. We show that, in sharp contrast to the classical mean-payoff objectives, some of the window mean-payoff objectives are decidable in games with partial-observation.

Connected through hyperedge HE-1 (induced by source paper "life is random time is not markov decision processes with window objectives"):
  with members:
    - "multi weighted markov decision processes with reachability objectives"
    - "expected window mean payoff"
    - "universal trees grow inside separating automata quasi polynomial lower bounds for parity games"
    - "the complexity of mean payoff games using universal graphs"
    - "extending finite memory determinacy by boolean combination of winning conditions"
    - "value iteration for long run average reward in markov decision processes"
    - "threshold constraints with guarantees for parity objectives in markov decision processes"
    - "a storm is coming a modern probabilistic model checker"

Connected through hyperedge HE-2 (induced by source paper "expected window mean payoff"):
  with members:
    - "stability in graphs and games"
    - "on the complexity of heterogeneous multidimensional quantitative games"
    - "the complexity of the kth largest subset problem and related problems"
    - "trading performance for stability in markov decision processes"
    - "looking at mean payoff and total payoff through windows"

Connected through hyperedge HE-3 (induced by source paper "on the complexity of heterogeneous multidimensional quantitative games"):
  with members:
    - "fixed dimensional energy games are in pseudo polynomial time"
    - "robust multidimensional mean payoff games are undecidable"
    - "looking at mean payoff and total payoff through windows"
    - "strategy synthesis for multi dimensional quantitative objectives"
    - "generalized mean payoff and energy games"

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.LO(Logic in Computer Science)