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: "approximate equilibria in games with few players"
  Abstract: We study the problem of computing approximate Nash equilibria (epsilon-Nash equilibria) in normal form games, where the number of players is a small constant. We consider the approach of looking for solutions with constant support size. It is known from recent work that in the 2-player case, a 1/2-Nash equilibrium can be easily found, but in general one cannot achieve a smaller value of epsilon than 1/2. In this paper we extend those results to the k-player case, and find that epsilon = 1-1/k is feasible, but cannot be improved upon. We show how stronger results for the 2-player case may be used in order to slightly improve upon the epsilon = 1-1/k obtained in the k-player case.

Connected through hyperedge HE-1 (induced by source paper "an empirical study on computing equilibria in polymatrix games"):
  with members:
    - "approximating nash equilibria in tree polymatrix games"
    - "from duels to battefields computing equilibria of blotto and other games"
    - "an empirical study of finding approximate equilibria in bimatrix games"
    - "coordination games on graphs"
    - "on the complexity of computing an equilibrium in combinatorial auctions"
    - "inapproximability of nash equilibrium"
    - "computing approximate nash equilibria in polymatrix games"
    - "computing nash equilibria of action graph games"

Connected through hyperedge HE-2 (induced by source paper "computing approximate nash equilibria in polymatrix games"):
  with members:
    - "an empirical study of finding approximate equilibria in bimatrix games"
    - "inapproximability of nash equilibrium"
    - "approximate well supported nash equilibria in symmetric bimatrix games"
    - "approximate well supported nash equilibria below two thirds"
    - "the complexity of non monotone markets"
    - "inapproximability of np complete variants of nash equilibrium"
    - "a direct reduction from k player to 2 player approximate nash equilibrium"
    - "settling the complexity of computing two player nash equilibria"

Connected through hyperedge HE-3 (induced by source paper "learning equilibria of games via payoff queries"):
  with members:
    - "the query complexity of correlated equilibria"
    - "finding approximate nash equilibria of bimatrix games via payoff queries"
    - "graphical models for game theory"
    - "on the communication complexity of approximate nash equilibria"
    - "query complexity of approximate nash equilibria"
    - "query complexity of correlated equilibrium"
    - "approximate well supported nash equilibria below two thirds"
    - "on the complexity of trial and error"

Connected through hyperedge HE-4 (induced by source paper "ranking games that have competitiveness based strategies"):
  with members:
    - "graphical models for game theory"
    - "approximate well supported nash equilibria below two thirds"
    - "on oblivious ptas s for nash equilibrium"
    - "discretized multinomial distributions and nash equilibria in anonymous games"
    - "an efficient ptas for two strategy anonymous games"
    - "settling the complexity of computing two player nash equilibria"

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)