human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "on equilibrium computation in biased games with quadratic penalties"):
  Abstract: Biased games were recently introduced by Caragiannis et al. as an extension of strategic-form games that can represent psychological biases of players towards certain pure strategies. They showed that for any number of players, and for a wide range of penalty functions that penalize players for deviating from their biases, a biased game admits a mixed-strategy equilibrium. We initiate the study of algorithms for finding approximate equilibria in two-player biased games. This problem is at least as hard as the analogous problem for bimatrix games, which has received much attention. For a natural subclass of two-player games with $L^2_2$ penalty functions, we characterize best responses and show how they can be computed by a strongly polynomial combinatorial algorithm. Building on this, we design the first polynomial-time algorithm that achieves a non-trivial approximation guarantee for these games. Furthermore, we study the existence of pure equilibria and we prove that games with bias functions in this class can have at most one pure equilibrium.

Includes members:
  Member "distributed methods for computing approximate equilibria":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "near optimal communication lower bounds for approximate nash equilibria")
  Member "the complexity of equilibria for risk modeling valuations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the complexity of computational problems about nash equilibria in symmetric win lose games")
  Member "on the complexity of nash equilibria in anonymous games":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ppp completeness with connections to cryptography")
  Member "computing approximate nash equilibria in polymatrix games":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "tree polymatrix games are ppad hard")
  Member "settling the complexity of computing two player nash equilibria":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning zero sum simultaneous move markov games using function approximation and correlated equilibrium")

Question: Please tell me which class the source paper 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)