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: "secondary spectrum market to acquire or not to acquire side information"
  Abstract: In a secondary spectrum market primaries set prices for their unused channels to the secondaries. The payoff of a primary depends on the channel state information (CSI) of its competitors. We consider a model where a primary can acquire its competitors CSI at a cost. We formulate a game between two primaries where each primary decides whether to acquire its competitor's CSI or not and then selects its price based on that. Our result shows that no primary will decide to acquire its competitor's CSI with probability $1$. When the cost of acquiring the CSI is above a threshold, there is a unique Nash Equilibrium (NE) where both the primaries remain uninformed of their respective competitor's CSI. When the cost is below the threshold, in the unique NE each primary randomizes between its decision to acquire the CSI or not. Our result reveals that irrespective of the cost of acquiring the CSI, the expected payoff of a primary remains the same.

Connected through hyperedge HE-1 (induced by source paper "the value of side information in secondary spectrum markets"):
  with members:
    - "quality sensitive price competition in spectrum oligopoly part ii"
    - "quality sensitive price competition in spectrum oligopoly"
    - "competition between wireless service providers pricing equilibrium and efficiency"
    - "competition with dynamic spectrum leasing"

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)