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: "computing strong nash equilibria for multiplayer games"
  Abstract: AbstractA new method for computing strong Nash equilibria in multiplayer gamesthat uses the theoretical framework of generative relations combined with astochastic search method is presented. Generative relations provide a meanto compare two strategy proﬁles and to assess their relative quality withrespect to an equilibria type. The stochastic method used, called AumannCrowding Based Diﬀerential Evolution (A-CrDE), uses a Diﬀerential Evo-lution algorithm that has been successfully used for numerical optimizationproblem. Numerical experiments illustrate the eﬃciency of the approach.Keywords:Non-cooperative games, strong Nash (Aumann) equilibrium, generativerelation, diﬀerential evolution1. IntroductionStrong Nash equilibrium (SNE) or Aumann equilibrium is one of themost appealing equilibrium concepts in non-cooperative game theory [1, 2, 3].Proposed by Aumann [4] as an alternative to the Nash equilibrium (NE),SNEs take into account the fact that some of the players, although havingnounilateral incentive todeviate, may beneﬁt (sometimes substantially) fromforming alliances/coalitions with other players. While in a NE no player canimprove its payoﬀ by unilateral deviation, in a SNE there is no coalitionof players that can improve their payoﬀs (by collective deviation). Thus,

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)