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: "shapley facility location games"
  Abstract: Facility location games have been a topic of major interest in economics, operations research and computer science, starting from the seminal work by Hotelling. Spatial facility location models have successfully predicted the outcome of competition in a variety of scenarios. In a typical facility location game, users/customers/voters are mapped to a metric space representing their preferences, and each player picks a point (facility) in that space. In most facility location games considered in the literature, users are assumed to act deterministically: given the facilities chosen by the players, users are attracted to their nearest facility. This paper introduces facility location games with probabilistic attraction, dubbed Shapley facility location games, due to a surprising connection to the Shapley value. The specific attraction function we adopt in this model is aligned with the recent findings of the behavioral economics literature on choice prediction. Given this model, our first main result is that Shapley facility location games are potential games; hence, they possess pure Nash equilibrium. Moreover, the latter is true for any compact user space, any user distribution over that space, and any number of players. Note that this is in sharp contrast to Hotelling facility location games. In our second main result we show that under the assumption that players can compute an approximate best response, approximate equilibrium profiles can be learned efficiently by the players via dynamics. Our third main result is a bound on the Price of Anarchy of this class of games, as well as showing the bound is tight. Ultimately, we show that player payoffs coincide with their Shapley value in a coalition game, where coalition gains are the social welfare of the users.

Connected through hyperedge HE-1 (induced by source paper "hotelling games with random tolerance intervals"):
  with members:
    - "from hotelling to load balancing approximation and the principle of minimum differentiation"
    - "fault tolerant hotelling games"
    - "hotelling games with multiple line faults"
    - "political discourse on social media echo chambers gatekeepers and the price of bipartisanship"
    - "hotelling games on networks existence and efficiency of equilibria"
    - "hotelling downs model with limited attraction"
    - "mechanism design with uncertain inputs to err is human to forgive divine"
    - "robust fault tolerant uncapacitated facility location"

Connected through hyperedge HE-2 (induced by source paper "from hotelling to load balancing approximation and the principle of minimum differentiation"):
  with members:
    - "hotelling downs model with limited attraction"
    - "location games on networks existence and efficiency of equilibria"
    - "on voting and facility location"
    - "voronoi game on graphs"
    - "on the power of deterministic mechanisms for facility location games"
    - "nash equilibria in voronoi games on graphs"

Connected through hyperedge HE-3 (induced by source paper "from recommendation systems to facility location games"):
  with members:
    - "convergence of learning dynamics in information retrieval games"
    - "a game theoretic approach to recommendation systems with strategic content providers"
    - "hotelling downs model with limited attraction"

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)