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: "to reach or not to reach efficient algorithms for total payoff games"
  Abstract: Quantitative games are two-player zero-sum games played on directed weighted graphs. Total-payoff games (that can be seen as a refinement of the well-studied mean-payoff games) are the variant where the payoff of a play is computed as the sum of the weights. Our aim is to describe the first pseudo-polynomial time algorithm for total-payoff games in the presence of arbitrary weights. It consists of a non-trivial application of the value iteration paradigm. Indeed, it requires to study, as a milestone, a refinement of these games, called min-cost reachability games, where we add a reachability objective to one of the players. For these games, we give an efficient value iteration algorithm to compute the values and optimal strategies (when they exist), that runs in pseudo-polynomial time. We also propose heuristics allowing one to possibly speed up the computations in both cases.

Connected through hyperedge HE-1 (induced by source paper "optimal reachability in divergent weighted timed games"):
  with members:
    - "simple priced timed games are not that simple"
    - "adding negative prices to priced timed games"
    - "a faster algorithm for solving one clock priced timed games"
    - "two player reachability price games on single clock timed automata"
    - "reachability time games on timed automata"

Connected through hyperedge HE-2 (induced by source paper "simple priced timed games are not that simple"):
  with members:
    - "adding negative prices to priced timed games"
    - "a faster algorithm for solving one clock priced timed games"
    - "two player reachability price games on single clock timed automata"

Connected through hyperedge HE-3 (induced by source paper "percentile queries in multi dimensional markov decision processes"):
  with members:
    - "unifying two views on multiple mean payoff objectives in markov decision processes"
    - "the complexity of the kth largest subset problem and related problems"
    - "exact and approximate determinization of discounted sum automata"
    - "variations on the stochastic shortest path problem"
    - "the odds of staying on budget"
    - "quantitative games with interval objectives"
    - "decidability problems for actor systems"
    - "markov decision processes with multiple long run averageobjectives"

Connected through hyperedge HE-4 (induced by source paper "variations on the stochastic shortest path problem"):
  with members:
    - "quantitative languages defined by functional automata"
    - "multiple environment markov decision processes"
    - "the odds of staying on budget"
    - "percentile queries in multi dimensional markov decision processes"
    - "expectations or guarantees i want it all a crossroad between games and mdps"
    - "what is decidable about partially observable markov decision processes with omega regular objectives"
    - "looking at mean payoff and total payoff through windows"
    - "computing quantiles in markov reward models"

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.GT(Computer Science and Game Theory)