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: "graphical models for game theory"
  Abstract: In this work, we introduce graphical modelsfor multi-player game theory, and give powerful algorithms for computing their Nash equilibria in certain cases. An n-player game is given by an undirected graph on n nodes and a set of n local matrices. The interpretation is that the payoff to player i is determined entirely by the actions of player i and his neighbors in the graph, and thus the payoff matrix to player i is indexed only by these players. We thus view the global n-player game as being composed of interacting local games, each involving many fewer players. Each player's action may have global impact, but it occurs through the propagation of local influences.Our main technical result is an efficient algorithm for computing Nash equilibria when the underlying graph is a tree (or can be turned into a tree with few node mergings). The algorithm runs in time polynomial in the size of the representation (the graph and theassociated local game matrices), and comes in two related but distinct flavors. The first version involves an approximation step, and computes a representation of all approximate Nash equilibria (of which there may be an exponential number in general). The second version allows the exact computation of Nash equilibria at the expense of weakened complexity bounds. The algorithm requires only local message-passing between nodes (and thus can be implemented by the players themselves in a distributed manner). Despite an analogy to inference in Bayes nets that we develop, the analysis of our algorithm is more involved than that for the polytree algorithm in, owing partially to the fact that we must either compute, or select from, an exponential number of potential solutions. We discuss a number of extensions, such as the computation of equilibria with desirable global properties (e.g. maximizing global return), and directions for further research.

Connected through hyperedge HE-1 (induced by source paper "complexity theory game theory and economics the barbados lectures"):
  with members:
    - "a round collapse theorem for computationally sound protocols or tfnp is hard on average in pessiland"
    - "on communication complexity of fixed point computation"
    - "near optimal communication lower bounds for approximate nash equilibria"
    - "query to communication lifting for bpp"
    - "lifting randomized query complexity to randomized communication complexity"
    - "settling the complexity of computing approximate two player nash equilibria"
    - "communication complexity of approximate nash equilibria"
    - "the price of anarchy in auctions"

Connected through hyperedge HE-2 (induced by source paper "smooth markets a basic mechanism for organizing gradient based learners"):
  with members:
    - "logan latent optimisation for generative adversarial networks"
    - "finite regret and cycles with fixed step size via alternating gradient descent ascent"
    - "a closer look at the optimization landscapes of generative adversarial networks"
    - "differentiable game mechanics"
    - "the mechanics of n player differentiable games"
    - "global convergence to the equilibrium of gans using variational inequalities"
    - "the numerics of gans"
    - "multiplicative weights update with constant step size in congestion games convergence limit cycles and chaos"

Connected through hyperedge HE-3 (induced by source paper "exploiting an adversary s intentions in graphical coordination games"):
  with members:
    - "security against impersonation attacks in distributed systems"

Connected through hyperedge HE-4 (induced by source paper "strategic prediction with latent aggregative games"):
  with members:
    - "the mechanics of n player differentiable games"
    - "learning to speed up structured output prediction"
    - "gans trained by a two time scale update rule converge to a nash equilibrium"
    - "learning graphical games from behavioral data sufficient and necessary conditions"
    - "learning with opponent learning awareness"
    - "the numerics of gans"
    - "cycles in adversarial regularized learning"
    - "on structured prediction theory with calibrated convex surrogate losses"

Connected through hyperedge HE-5 (induced by source paper "graphical one sided markets"):
  with members:
    - "schelling games on graphs"
    - "swap stability in schelling games on graphs"
    - "maximin share allocations on cycles"
    - "schelling segregation with strategic agents"
    - "fair allocation of indivisible items with externalities"
    - "almost envy free allocations with connected bundles"
    - "fair division of a graph"
    - "fair division via social comparison"

Connected through hyperedge HE-6 (induced by source paper "provable computational and statistical guarantees for efficient learning of continuous action graphical games"):
  with members:
    - "learning quadratic games on networks"
    - "learning graphical games from behavioral data sufficient and necessary conditions"
    - "targeting interventions in networks"
    - "from behavior to sparse graphical games efficient recovery of equilibria"
    - "on influence stable behavior and the most influential individuals in networks a game theoretic approach"
    - "estimating diffusion network structures recovery conditions sample complexity soft thresholding algorithm"
    - "learning the structure and parameters of large population graphical games from behavioral data"
    - "on the complexity of nash equilibria of action graph games"

Connected through hyperedge HE-7 (induced by source paper "the impact of tribalism on social welfare"):
  with members:
    - "on linear congestion games with altruistic social context"
    - "bounding the inefficiency of altruism through social contribution games"
    - "friendship altruism and reward sharing in stable matching and contribution games"
    - "how bad is forming your own opinion"

Connected through hyperedge HE-8 (induced by source paper "be a leader or become a follower the strategy to commit to with multiple leaders extended version"):
  with members:
    - "multidefender security games"
    - "a general framework for computing optimal correlated equilibria in compact games"
    - "polynomial time computation of exact correlated equilibrium in compact games"

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)